AI Ethics and Responsible AI Use Policy

Preamble

This Confidentiality and Non-Disclosure Policy (“Policy”) establishes the requirements for protecting confidential and sensitive information within Humanics Global Advisors (HGA). HGA’s mission as an AI-driven global advisory firm is to connect skilled consultants with development opportunities through a secure digital platform and a success-fee business model. In doing so, HGA handles sensitive personal data, client project information, bid/proposal documents, and other confidential materials that must be safeguarded to maintain trust and comply with legal and ethical standards.

Scope: This Policy applies to all individuals and entities with access to HGA’s information or systems, including but not limited to: – HGA employees and internal staff, – External consultants engaged by or via HGA, – Partner organizations, clients, or donor representatives using HGA’s digital platform or services, – Any other authorized users of the HGA Digital Platform (formerly known internally by a different project name).

All such persons are collectively referred to as “Users” or “Authorized Users” under this Policy. Compliance with this Policy is mandatory. Each User must read, understand, and adhere to these rules as a condition of their engagement with HGA. The Policy covers all forms of information (electronic, paper, oral) related to HGA’s business, and it remains in effect at all times, including outside of normal business hours and after a person’s contract or employment with HGA ends. The goal is to protect the confidentiality, integrity, and availability of information assets while enabling HGA’s collaborative, technology-driven operating model.

Executive Summary

For the purpose

This Policy provides a comprehensive framework for the ethical and responsible use of AI on the HGA Digital Platform. It begins with a formal Preamble affirming HGA’s commitment to global AI ethics standards and continues with an Executive Summary and Definitions to clarify key terms. The Policy then sets forth core principles – Fairness and Non-Discrimination; Transparency and Explainability; Human Oversight and Accountability; Privacy and Data Protection; Security and Resilience; Auditability and Traceability; and User Rights (Contestability and Appeal) – that must guide all AI system development and use at HGA. These principles are drawn from widely endorsed guidelines (UNESCO, OECD, etc.) and are integrated into HGA’s operational practices. Subsequent sections delineate how HGA will implement these principles in practice, including specific role-based responsibilities (for Platform users such as Business Developers, Consultants, System Managers, etc.), timelines for policy implementation and reviews, and governance mechanisms like internal audits and oversight committees. The Policy also details requirements for documentation and reporting, procedures for managing any breach or incident (and taking corrective action), and the enforcement measures and sanctions for non-compliance. Importantly, this document highlights HGA’s legal and ethical obligations – including compliance with data protection laws like GDPR and CCPA, and adherence to donor-imposed ethical standards such as the World Bank’s Consultant Guidelines. In summary, HGA is instituting a robust AI ethics governance program to ensure that all AI use not only achieves business objectives but also protects individual rights, promotes trust, and aligns with global best practices. All users of the HGA Digital Platform are required to understand and follow this Policy, and HGA will support them through training, tools, and a culture of ethical accountability.

s of this Policy, the following key terms are defined:

Confidential Information: Confidential Information means any non-public information related to HGA or its business partners that is disclosed, learned, or developed in the course of HGA’s operations, and which a reasonable person would understand to be private or proprietary in nature. This includes, without limitation, HGA’s business strategies, financial information (e.g. pricing, fees, margins), client or donor lists and contacts, project opportunities, proposals and bids, internal processes, software code or algorithms, and any proprietary templates or tools used by HGA[1]. It also includes information entrusted to HGA by others: for example, Consultant information (such as personal data in CVs, identification documents, professional references, or any proprietary methodologies a consultant shares with HGA for a project)[2], and Client information (such as project requirements, technical data, reports, records, trade secrets, or any deliverables and work product prepared for a client’s project)[3]. Bid and project materials (including proposals, contracts, and project deliverables prepared for clients) are considered Confidential Information of HGA and/or the client. Information need not be marked “confidential” to be protected; if its nature or the circumstances of access imply it is sensitive, it should be treated as Confidential Information.

Certain standard exceptions apply: Confidential Information does not include information that (a) becomes publicly available without breach of any obligation (e.g. published reports or information released by the owner); (b) was rightfully known or possessed by the receiving party before disclosure by HGA or its clients, as evidenced by written records; (c) is independently obtained from a third party who had the legal right to disclose it without confidentiality restrictions; or (d) is independently developed by a receiving party without use of or reference to HGA’s or a client’s confidential information[4].

Personal Data: Personal Data refers to any information that relates to an identified or identifiable individual. This includes, for example, contact details (names, addresses, telephone numbers, email), personal identifiers (date of birth, government ID or social security numbers, passport or tax ID numbers), biographical data (resumes/CVs, educational and work history, certifications, photos), financial account information, and any other data that can be used to identify a person[5]. Personal Data is considered a special category of Confidential Information that requires a high degree of protection. Under this Policy and applicable laws, Personal Data must be handled with strict confidentiality and care, and its use is limited to the purposes for which it was collected. (Note: In some jurisdictions Personal Data may be referred to as “personally identifiable information” or “personal information.” All such terms are encompassed herein.)
Authorized Users: Authorized Users are individuals who have been granted access to HGA’s information, network, or digital platforms by virtue of their role or relationship with HGA. This includes HGA employees and contractors, registered consultants using the HGA Digital Platform, approved representatives of client or partner organizations, HGA’s business associates, and any other persons who have been given login credentials or permission to handle HGA data. Authorized Users are only permitted to access information and systems as necessary for their duties (see Section 3 on Access Control) and must be covered by appropriate agreements (employment contracts, consulting agreements, platform user terms, NDAs, etc.) that include confidentiality obligations. Each Authorized User is individually responsible for safeguarding the credentials and data entrusted to them.
HGA Digital Platform (“the Platform”): The secure online platform provided by HGA that enables consultants, organizations (clients/donors), and HGA staff to collaborate on consulting opportunities and projects. Users of the Platform can create and manage consultant profiles, post and apply for consultancy listings, exchange communications, store project documents, and track deliverables and payments in a centralized system[6][7]. The HGA Digital Platform incorporates advanced features such as AI-driven matching of consultants to opportunities (including automated generation of tailored resumes and applications) and robust security controls. All data on the Platform is hosted in a secure environment with encryption, authentication, and audit logging (see Section 6 Security Controls). Use of the Platform is subject to this Policy and any applicable Terms of Use. (Note: The Platform was previously referred to under a development codename; this Policy will only refer to it as the HGA Digital Platform.)

Other definitions: In this Policy, “HGA” or the “Company” refers to Humanics Global Advisors (and its affiliated entities), and “Users” refers collectively to all persons within scope of this Policy. The term “information” may encompass data in any form, including oral discussions. “Systems” or “IT systems” refers to HGA’s computers, network, cloud services, communication tools, and the HGA Digital Platform itself. “Policy Administrator” is the HGA management designee responsible for this Policy (e.g. Data Protection Officer or Security Officer).

Definitions

For purposes of this Policy, the following definitions apply:

Artificial Intelligence (AI) – Any system, tool, or software that performs tasks which would typically require human intelligence. This includes but is not limited to machine learning models, predictive analytics, natural language processing, decision support systems, and any algorithmic recommendations or automated decision-making processes used on the HGA Digital Platform. For clarity, HGA adopts a broad definition of AI consistent with international standards – AI systems are those capable of processing data in a way that resembles intelligent behavior or human decision-making.
AI System – An implemented instance of AI software or model performing a specific function (e.g., an AI-driven feature that matches consultants to projects or an automated proposal scoring tool). An AI System may involve various components such as data inputs, algorithms, and outputs that inform or automate decisions.
HGA Digital Platform (the “Platform”) – The online system provided by Humanics Global Advisors for facilitating consulting engagements, including modules for consultant profiles, project listings, AI-driven matching or application assistance, and related collaboration tools. All references to the Platform in this Policy refer to the integrated environment (previously in development under the name “DevTender”) through which HGA, consultants, and client organizations interact.
Platform Users – All individuals who access or use the HGA Digital Platform, including Consultants (external independent professionals offering services via HGA), Client Organizations (external entities or donors posting or funding projects), and HGA Staff (internal personnel managing or supporting platform operations). Within HGA Staff, specific roles are defined below (see “Roles and Responsibilities”), such as Business Developers, System Managers, Receivables/Payables Officers, etc.
Personal Data – Any information relating to an identified or identifiable natural person (“Data Subject”), as defined under applicable data protection laws (e.g., names, contact information, CV details, identification numbers, online identifiers, or factors specific to a person’s identity). Personal Data includes any data that can directly or indirectly identify an individual, and encompasses “personal information” as defined in laws like GDPR and CCPA.
Processing – Any operation performed on Personal Data, whether by automated means or not, including collection, recording, organizing, storing, altering, retrieving, using, disclosing, or deleting such data.
Bias – In the context of AI, bias refers to systematic error or deviation in an AI system’s outcomes that leads to unfair or prejudiced results against certain individuals or groups. Bias can stem from skewed training data, flawed algorithms, or inappropriate use, and may result in discrimination (see below).
Discrimination – Unjust or prejudicial treatment of individuals or groups based on inherent or protected characteristics (such as race, gender, ethnicity, age, religion, etc.) or other factors. In AI systems, discrimination can occur if outputs disproportionately advantage or disadvantage certain groups in violation of fairness principles or equal opportunity norms.
Transparency – The quality of an AI system being understandable and open to inspection by stakeholders. Transparency involves providing clear, accessible information about how an AI system operates (its algorithms, data sources, decision logic) and making users aware when they are interacting with or subject to an AI.
Explainability – The ability to explain in understandable terms the logic, factors, and reasoning behind an AI system’s output or decision. Explainability is a component of transparency focused on making the AI’s behavior interpretable to humans (developers, users, or affected parties).
Human Oversight – Active human involvement in the operation of an AI system, including the ability to monitor, review, and intervene in automated processes. Human oversight ensures that automated decisions can be checked and, if necessary, overridden by human decision-makers, thereby preventing unchecked “black box” automation.
Accountability – The principle that individuals or entities (and specific roles within HGA or among Platform users) are answerable for the ethical and proper functioning of AI systems. Accountability includes the duty to ensure compliance with this Policy and applicable laws, and to address any negative impacts or violations that may arise from AI use.
Data Protection Laws – Refers to applicable statutes and regulations governing privacy and personal data, notably the EU General Data Protection Regulation (“GDPR”) and the California Consumer Privacy Act (“CCPA”), among others. These laws impose obligations on how Personal Data is processed, requiring measures for privacy, security, transparency, and user rights.
GDPR – The European Union’s General Data Protection Regulation 2016/679. GDPR is a comprehensive privacy law setting standards for data protection, including principles like lawfulness, fairness, transparency, purpose limitation, data minimization, accuracy, storage limitation, integrity and confidentiality, and accountability. It also grants individuals specific rights over their personal data (such as access, rectification, erasure, objection, and restrictions on automated decision-making).
CCPA – The California Consumer Privacy Act of 2018 (as amended by the California Privacy Rights Act). CCPA grants California residents rights regarding their personal information (such as the right to know, delete, opt-out of sale, and non-discrimination) and imposes duties on businesses to safeguard personal data and be transparent about data practices.
Donor Ethical Guidelines – Requirements and codes of conduct imposed by clients or funding organizations (such as international development agencies or multilateral development banks) that govern ethical behavior, anti-corruption, fairness, and transparency in consulting engagements. For example, the World Bank’s Consultant Guidelines and Anti-Fraud & Corruption guidelines demand that consultants “observe the highest standard of ethics” and avoid conflicts of interest in executing contracts[3]. HGA and all Consultants must adhere to such donor requirements when applicable.
Auditability – The capacity for an AI system’s processes and outcomes to be audited – that is, examined and verified after the fact. Auditability usually requires maintaining traceability (records/logs of data sources, system inputs, decision pathways, and outputs) so that an AI’s behavior can be reconstructed and evaluated for compliance with ethical and legal standards.
User Rights – The rights afforded to individuals (especially data subjects or those subject to AI-driven decisions) to receive information, provide input, or seek recourse regarding AI system operations. Key user rights in this context include the right to be informed about AI use, the right to an explanation of algorithmic decisions, and the right to contest or appeal decisions made by AI (seeking human review or intervention, as recognized by laws like GDPR[4]).

(Note: Other technical or legal terms used in this Policy shall be interpreted consistently with their meaning under relevant laws or industry standards. In case of doubt, the Chief System Manager or legal counsel should be consulted for clarification.)

Fairness and Non-Discrimination

Policy Statement: HGA is committed to fairness in all AI-supported functions of the Platform and will proactively prevent discrimination or biased outcomes. No AI system used by HGA shall treat individuals or groups unfairly on the basis of protected characteristics or socioeconomic factors. We embrace the principle that AI actors should make all reasonable efforts to minimize or avoid discriminatory or biased outcomes throughout the AI system lifecycle to ensure fairness[5]. This means that from initial design to deployment and ongoing use, AI models must be developed and tested with fairness as a paramount criterion.

Non-Discrimination Measures: All algorithms, training data, and AI-driven processes will be vetted for potential bias. HGA will perform regular bias audits and fairness tests on AI systems, using diverse and representative data sets to the extent possible, to detect and correct any skew or disparate impact. In practice:

Inclusive Design: AI development should involve input data that represent the diversity of HGA’s user base (e.g. consultants of different genders, nationalities, backgrounds) to avoid marginalizing any group. Designers must exclude attributes or proxies that are discriminatory (for instance, avoiding variables that directly or indirectly act as proxies for race, gender, etc., unless justified and mitigated).
Bias Impact Assessment: Before an AI system is rolled out, HGA will conduct an Ethical Impact Assessment or similar review focusing on fairness (aligned with UNESCO’s guidance on “readiness assessment and impact assessment ethics” for AI[6]). This includes testing the system for differential outcomes across demographic groups. Any identified bias must be addressed (e.g. retraining the model, adjusting parameters, or augmenting data) prior to full deployment.
Ongoing Monitoring: Fairness is not a one-time concern. The System Manager (and any assigned AI Ethics Committee or officer) shall continuously monitor AI outputs for signs of unfair bias. If an AI-driven recommendation or decision is found to consistently favor or disfavor a particular group without a valid reason, the system will be paused and re-evaluated.
Human Review for Sensitive Decisions: For high-stakes decisions (such as selection of consultants for projects or awarding opportunities), AI suggestions or scores shall not be the sole determinant. Human decision-makers (e.g. Business Developers or project managers) must review AI outputs and exercise judgment, especially if there is any indication that an automated ranking may reflect bias. HGA policy mandates human-in-the-loop oversight to correct potential biases that the AI may introduce.

Equal Opportunity: In alignment with OECD’s AI Principles, HGA reinforces that AI should respect human rights, including the values of non-discrimination, equality, and social justice[7]. All Platform users will have equal access to AI tools or benefits; for example, if an AI tool assists with proposal writing or matching consultants to projects, it will be made available in a manner that does not unjustly favor certain users over others. HGA also aligns with donor expectations of fairness – for instance, the World Bank’s procurement guidelines underscore that fairness and transparency in selection mean no consultant should gain an improper competitive advantage[8]. We echo this standard: AI will not be used to give any user an undue edge; rather, it will serve to impartially improve efficiency and outcomes for all parties.

HGA recognizes that unchecked AI can inadvertently perpetuate existing societal biases[9]. Therefore, maintaining fairness is a continuous obligation under this Policy. Any stakeholder who believes an AI tool or decision on the Platform may be biased or discriminatory should report it (see Reporting and Documentation section), and HGA will promptly investigate and remediate as needed. Engendering trust through fairness is critical to HGA’s mission, and we will take all necessary steps – technical, procedural, and organizational – to uphold this principle.

Transparency and Explainability

Policy Statement: HGA’s AI systems must operate with appropriate transparency. We will clearly disclose when and how AI is used on the Platform, provide understandable explanations for AI-driven outcomes, and ensure that users can inquire about and understand the basis of decisions that affect them. Transparency is fundamental to building trust and is mandated both by ethical norms and legal requirements. As the OECD Principles state, AI actors should commit to transparency and responsible disclosure regarding AI systems, providing meaningful information about AI so that stakeholders are aware of AI involvement and can understand outcomes[10].

AI Use Disclosure: The HGA Digital Platform will inform users whenever they are interacting with an AI system or subject to an AI-assisted decision. This disclosure may be provided via user interface cues, labels, or policy notices. For example, if an AI algorithm ranks consultant applications or suggests matches, the Platform will indicate that “AI recommendations” were used in that process. Users (consultants, organizations, or HGA staff) will not be misled into thinking a decision was entirely human if in fact AI played a significant role. We align with the principle of inclusive transparency, ensuring all users – regardless of technical background – know when AI is in effect.

Explanations of AI Decisions: Beyond mere disclosure, HGA will strive for explainability of AI outcomes. Upon request (and where feasible, automatically for significant decisions), the Platform will provide an explanation or reasoning for AI-driven results in a clear, non-technical manner. For instance, if an AI system scores consultant candidates for a project, the factors that influenced a particular score or ranking (experience level, skill match, past performance metrics, etc.) should be explainable. This may involve providing users with key criteria or a summary of how the AI model arrived at its output. Any limitations of the AI (e.g., confidence level or data quality issues) will also be communicated when relevant, so that decisions can be contextualized.

Responsible Disclosure: Consistent with OECD guidance, HGA will provide meaningful information appropriate to the context about our AI systems[10]. This includes maintaining up-to-date documentation on AI model purposes, data sources, and logic, and making such documentation available to stakeholders (internal or external auditors, and in certain cases, to users or clients for transparency). While we must balance transparency with the protection of intellectual property and security, HGA will err on the side of openness, especially where an AI decision has significant impact on individuals’ opportunities or rights.

Training for Staff and Clarity for Users: HGA will train its staff (especially those in roles like Business Developers or System Managers) to understand the AI systems sufficiently so that they can explain outcomes to affected users or clients. We will also create user-friendly guides or FAQs about how AI features on the Platform work. For example, if the Platform uses an “AI Agent” to assist Consultants in writing proposals, we will publish guidance on what the AI does, what inputs it uses, and how the Consultant can review or edit the AI-generated content. This empowers users to engage with AI tools knowingly and effectively.

Record of Logic and Data: To facilitate both explainability and future audits, HGA ensures that AI systems are built with traceability (see Auditability section). At a minimum, for each automated decision of consequence, the system should be able to log the key factors or data points that influenced that decision. This record can then be used to reconstruct an explanation if needed. For complex models (like machine learning algorithms that are less interpretable), HGA will use techniques like feature importance analysis or sample case explanations to extract understandable reasoning.

In summary, HGA commits to a “no black box” approach for AI that affects people’s opportunities or data. By being transparent and providing explanations, we uphold individuals’ right to be informed and we align with emerging legal norms (e.g., the implied “right to explanation” under GDPR Recital 71 and related provisions[11]). Transparency and explainability are not only ethical obligations but also prerequisites for accountability and trust – users who understand AI decisions are better positioned to accept them or challenge them, which ultimately improves the quality and fairness of our services.

Human Oversight and Accountability

Policy Statement: HGA will ensure that AI systems on the Platform remain under meaningful human control and that clear accountability for AI outcomes is maintained. Human oversight is mandated for all critical AI functions: at no point will HGA deploy AI in a fully autonomous manner without a responsible human in the loop or at least in a supervisory role. Furthermore, specific individuals and roles are assigned accountability to oversee ethical compliance of AI (see “Roles and Responsibilities” below). Accountability means that HGA personnel and partners cannot abdicate responsibility to an algorithm; instead, they must treat AI as an aid to human decision-making, not a replacement for it. As UNESCO’s global Recommendation emphasizes, the importance of human oversight of AI systems must always be remembered[1]. Likewise, the OECD calls for mechanisms to ensure capacity for human agency and oversight, especially to address risks from misuse or unintended outcomes[12].

No Fully Automated Decision without Recourse: Any AI-driven decision that significantly affects individuals (such as hiring a consultant for a project, evaluating performance, or other consequential matters) shall not be final without the possibility of human intervention. HGA guarantees that users have the ability to request human review of automated outcomes (see User Rights section for the formal appeals process). Internally, HGA’s Business Developers or managers must review AI-generated recommendations and have the authority to override them if they are flawed or raise ethical concerns. For example, if an AI recommendation for awarding a contract appears to disadvantage certain qualified applicants, the responsible manager must investigate and can adjust the decision as appropriate.

Defined Oversight Roles: HGA designates the System Manager (and any future AI Ethics Committee or Chief AI Ethics Officer if established) as primarily responsible for overseeing the ethical operation of AI systems. This includes reviewing system design documents, validation reports, and audit findings. The System Manager has the mandate to halt or require modifications to an AI system that is not meeting our ethical criteria. Additionally, Business Developers (who interface with client projects and consultant selection) are accountable for ensuring that AI suggestions are used fairly and consistently, and for providing necessary human judgment in final decisions. Each Consultant user also has a degree of oversight in that they can see and modify AI-assisted content (e.g., if an AI helps draft a proposal, the Consultant reviews and edits it before submission).

Accountability Framework: In accordance with OECD’s principle of Accountability, AI actors (HGA staff and any partners involved in AI) are accountable for the proper functioning of AI systems and for compliance with the above principles[13]. HGA implements this by:

Assigning Responsibility: For each AI system or feature on the Platform, a specific owner (usually a System Manager or product manager) is assigned. That owner is responsible for the system’s ethical performance, documentation, and maintenance. Their duties include ensuring the AI is developed following this Policy, monitoring its outputs over time, and initiating periodic reviews.
Traceability and Logging: We maintain detailed logs of AI system activities – including data used for training or decisions, model versions, and decision outputs – to enable after-the-fact accountability. This traceability supports internal audits and any needed external inquiries, as one can reconstruct how a decision was made[14]. If an outcome is questioned, we should be able to trace which inputs and algorithm led to it, and who oversaw the process.
Risk Management: Accountable AI management means anticipating and mitigating risks. HGA employs a risk management approach at each phase of the AI lifecycle[15]. This involves identifying potential ethical or legal risks (bias, security, etc.) during design, testing these during development, and monitoring during deployment. Responsible personnel must document these risks and the measures taken to address them (such as bias mitigation strategies or data privacy safeguards). If new risks emerge (e.g., an AI model behaving unexpectedly in production), accountability requires prompt action to diagnose and correct issues.
Escalation Protocol: HGA establishes clear protocols for staff to raise concerns about AI behavior. If any team member (developer, business user, etc.) suspects an AI system is causing harm or violating this Policy, they are empowered and obligated to escalate the issue to the System Manager or an executive oversight body. There will be no retaliation for raising good-faith concerns; on the contrary, doing so is part of responsible duty. Once raised, the issue will be reviewed and, if substantiated, corrective steps taken (including potentially suspending the AI system until fixed).

By integrating human oversight at multiple levels and delineating accountability, HGA ensures that AI remains a tool to be directed by human values and judgment. This dual approach – humans oversee AI and humans are accountable for AI – guards against automation bias (over-reliance on algorithmic output) and ensures alignment with our ethical commitments at all times. Ultimately, accountability for AI in HGA rests with senior leadership as well: management will receive periodic reports on AI performance and compliance, and will support a culture where ethical AI use is a shared responsibility across the organization.

Privacy and Data Protection in AI Systems

Policy Statement: Any AI system or process within the HGA Digital Platform that involves personal data must rigorously safeguard privacy and comply with all applicable data protection laws and regulations. Privacy by design and data protection by design are required standards: we will design AI systems with built-in privacy controls (minimizing personal data use, securing data, and respecting user privacy preferences). HGA acknowledges its legal obligations under frameworks such as the EU GDPR and the CCPA, and we affirm that we handle personal information in compliance with these laws, adopting global best practices for data privacy[16].

Lawful Basis and Minimization: Before deploying an AI that processes personal data (e.g. analyzing consultant profiles or evaluating performance metrics), HGA will ensure there is a lawful basis for that processing (such as the individual’s consent, contractual necessity, or legitimate interest in accordance with GDPR Article 6). Personal data used in AI will be limited to what is necessary for the stated purpose (data minimization). For example, if an AI matches consultants to jobs, it will use relevant professional data (skills, experience, prior ratings) but not extraneous personal details unrelated to merit. Sensitive personal data (such as racial or ethnic origin, health information, etc.) will not be processed by AI unless absolutely necessary and legally permitted with explicit consent or other safeguards (GDPR Article 9 conditions).

Transparency in Data Use: In line with transparency principles, HGA will inform users about what personal data is used in AI models or decisions. Our privacy notices and AI-specific disclosures will specify categories of data processed, sources of data, and the purposes of processing[17]. Users will have access to their personal data and the ability to correct or update it if needed, ensuring that AI systems are relying on accurate information (supporting the GDPR principle of accuracy).

Protecting Personal Data in AI Lifecycle: We apply strong privacy protections at each stage:
– Data Collection: Only collect personal data that is needed for Platform functionality or AI features. Whenever feasible, use anonymization or pseudonymization for AI training data to avoid using directly identifiable information.
– Data Storage: Personal data used for AI will be stored securely with appropriate access controls and encryption. The Platform’s databases (including those enumerated in our system specifications, such as consultant information tables) are governed by HGA’s data security policies (see Security section). We also adhere to retention limits – personal data is not kept longer than necessary for the AI’s purpose (consistent with storage limitation principles).
– Model Training: If AI models are trained on historical data (e.g., records of past project awards), we will assess that data for any inherent biases or privacy issues. Training data sets containing personal information of EU residents will be handled per GDPR (which may require a Data Protection Impact Assessment (DPIA) if training poses high privacy risks). We favor using aggregated or de-identified data for training when possible.
– Inference/Decision Phase: When an AI is running and making decisions about individuals, the system will apply any applicable privacy rules – for instance, if a user has opted out of certain data uses, the AI should respect that and exclude such data from its analysis.

Data Subject Rights and Automated Decisions: GDPR grants individuals rights specifically in context of automated decision-making, including the right not to be subject to decisions based solely on automated processing that have significant effects, unless certain conditions are met (GDPR Art. 22). HGA will not deploy AI in a manner that violates these provisions. In any case where the Platform’s AI contributes to an important decision about a person, we will either (a) ensure a human is meaningfully involved in the decision (thus taking it out of “solely automated” scope), or (b) obtain explicit consent from the individual for the automated process if it must be solely automated and allowed by law. Additionally, we recognize and facilitate users’ rights to: obtain human intervention, express their point of view, and contest the decision[4] – these rights are addressed in detail in the User Rights section, but are mentioned here as a key privacy protection as well.

Cross-Border Data and Client Data: As HGA operates internationally (and may host data in the U.S. or other jurisdictions), we comply with cross-border data transfer rules. Users are informed and consent to the transfer of their data across borders as needed for Platform functionality[16]. We use approved transfer mechanisms (such as Standard Contractual Clauses for EU data) if required. Moreover, if our AI systems utilize data provided by clients or donor organizations, we ensure that any such use is authorized and in compliance with those parties’ privacy commitments. HGA will not repurpose client-provided personal data for AI training or development without permission and will honor all confidentiality agreements.

Confidentiality and Privacy Training: All HGA staff and any contractors who work with AI systems must sign confidentiality agreements and receive training on data protection obligations. The importance of privacy compliance – including handling of consultant personal data in the Platform’s AI features – is reinforced in HGA’s internal policies and contracts (as seen in our Consultant Agreement commitments to GDPR/CCPA compliance[16]). Employees who fail to follow privacy requirements will face disciplinary measures (see Enforcement section).

In essence, HGA’s approach to AI is privacy-centric. We recognize that AI’s power must not come at the expense of individuals’ privacy rights. By embedding data protection measures and strictly following laws like GDPR and CCPA, we not only avoid legal penalties but also ensure that our Platform users maintain control over their personal information and feel secure using our AI features. Our donors and partners similarly demand this high standard, and HGA will continuously audit and improve its privacy practices as regulations evolve (for instance, adapting to new laws or amendments in relevant jurisdictions).

Security and Resilience of AI Systems

Policy Statement: HGA will maintain robust security for all AI systems and the data they process, to prevent unauthorized access, manipulation, or malfunction that could lead to ethical breaches or harm. We commit to ensuring that AI systems are robust, secure, and safe throughout their entire lifecycle[18]. This includes technical measures to protect against hacking and data breaches, as well as design strategies to make AI outputs reliable and resilient against failures or misuse.

Technical Security Controls: The AI components of the HGA Platform will be protected by the same high standards that apply to our overall IT infrastructure, plus additional safeguards pertinent to AI:
– Access Control: Only authorized personnel (System Managers, designated developers) can access AI model code, training data, or configuration settings. Role-based access control is implemented so that, for example, a Business Developer can see AI-generated recommendations via the Platform interface, but cannot directly alter the underlying AI model. All access to sensitive AI resources is logged.
– Data Security: Any personal data used by AI is encrypted at rest and in transit. We use secure databases (as outlined in our technical specifications) for storing data like consultant profiles, and apply encryption and network security to APIs that feed data into AI algorithms. If the AI uses any external APIs or services (e.g., an AI language model via a third-party provider), we ensure those communications are encrypted and that the third-party adheres to privacy and security commitments.
– Adversarial Robustness: HGA will evaluate AI systems for susceptibility to adversarial inputs or manipulation. For instance, we consider whether someone could “game” the AI (e.g., by inputting false data in their profile to unfairly boost their ranking). We put checks in place (data validation, anomaly detection) to reduce such vulnerabilities. The System Manager will stay informed of security research on AI (like adversarial attacks on machine learning) and apply patches or improvements as needed to maintain robustness.
– Fail-Safe Mechanisms: Consistent with OECD guidance, mechanisms are in place to ensure that if an AI system behaves unexpectedly or poses risk, it can be overridden, paused, or safely decommissioned[19]. For example, if an AI service is outputting obviously incorrect or harmful results (perhaps due to a software bug or corrupted model), the System Manager or on-call administrator has the ability to disable that service and revert to a manual process until the issue is resolved. AI systems are monitored in real time for performance anomalies or errors, with alerts set to notify technical staff of any critical failures.

Resilience and Reliability: Beyond guarding against malicious threats, HGA designs AI systems to be reliable in normal and foreseeable conditions. This involves rigorous testing and quality assurance:
– Testing: AI models are tested not only for accuracy but also for stability – how do they perform if input data is noisy or edge-case? We simulate various scenarios (including worst-case or “stress” conditions) to ensure the AI response remains within safe bounds. For instance, if an AI matching algorithm receives incomplete data about a consultant, it should fail gracefully (perhaps asking for more information) rather than making a random guess.
– Redundancy: Where appropriate, we incorporate redundancy or fallback systems. If an AI feature fails, the Platform may have a non-AI fallback. For example, if an AI that auto-screens consultant applications goes down, applications will be forwarded to human reviewers so that operations continue.
– Updates and Patches: The System Manager is responsible for keeping AI software up to date. Security patches for any AI libraries or frameworks will be applied promptly to fix known vulnerabilities. When models are updated or retrained, the process includes verifying that no new security issues have been introduced and that model performance remains within expected parameters.
– Third-Party Components: If using third-party AI tools or pre-trained models, HGA will vet those for security (ensuring they come from reputable sources, are licensed correctly, and have no known backdoors). We will also monitor external advisories; for example, if an open-source AI tool we use is later found to have a security flaw or ethical issue, we will address it (patch, configuration change, or replacement).

Incident Response for AI Security: In the event of a security incident involving an AI system (e.g., a data breach of training data, unauthorized model access, or detection of manipulation of AI outputs), HGA will invoke its Incident Response Plan (see Breach Management section for details). Specific to AI, this may include: immediately isolating the affected system, analyzing the extent of compromise, removing any tainted data or model components, and validating the integrity of outputs. We will also assess whether the incident led to any biased or incorrect decisions and take corrective action if so (for example, re-evaluating any decisions made by a compromised AI during the period of incident).

Compliance with Standards: HGA’s security practices for AI align with industry standards and regulations. We consider guidelines such as ISO/IEC 27001 for information security management and emerging AI-specific standards (ISO/IEC 23894 on AI risk management, etc.) as benchmarks. Additionally, donor organizations often require stringent security for systems handling project data; we treat those requirements as minimum baselines. By securing AI, we not only protect data and operations but also uphold the trust that users and clients place in our Platform. Security lapses in AI can directly translate to ethical lapses (for instance, if someone hacks an AI to produce biased results). Thus, maintaining security is an ethical imperative integral to this Policy.

Auditability and Traceability

Policy Statement: HGA will ensure that all AI systems are designed and deployed in a manner that is auditable. Auditability means that we maintain records and documentation sufficient to trace and review how AI systems function and the decisions or recommendations they produce. This capability is crucial for verifying compliance with this Policy, investigating incidents, and demonstrating accountability to external stakeholders (clients, regulators, or auditors). In line with OECD’s accountability principle, we strive to ensure traceability in relation to datasets, processes, and decisions made during the AI system lifecycle[14].

Documentation of AI Systems: For each AI tool or feature, HGA will create and maintain up-to-date documentation that includes: the purpose of the AI system, its developer/owner, the algorithm or model architecture used, training data characteristics, validation results (accuracy, bias tests, etc.), and any constraints or known limitations. This documentation acts as a reference for auditors and developers. It will also record any changes or updates to the system (version history), ensuring we have an audit trail of modifications. Example: If the Platform uses a machine learning model to score consultant proposals, we will document the model version, when it was trained and on what data, its accuracy metrics, and any adjustments made after deployment.

Logging of AI Operations: The Platform will log AI system activities in a secure and tamper-evident manner. The logs should capture events such as: when an AI makes a significant decision or recommendation, what input data was used for that decision, which version of the model was in operation, and to whom the output was delivered. Additionally, any manual override or human intervention on an AI decision should be logged (e.g., “On 2025-08-01, AI recommended Candidate A; human manager overrode and selected Candidate B”). These logs are essential for post-hoc analysis and are part of our traceability fabric. HGA will treat these log records as sensitive data (since they might contain personal data or business-sensitive information) and secure them accordingly.

Regular Audits and Reviews: HGA will conduct periodic internal audits of AI systems (at least annually, with frequency increasing for higher-risk systems). The audit will be carried out by an internal auditor or committee independent of the day-to-day AI development team (or by an external auditor/consultant where appropriate) to ensure impartiality. The audit will cover: compliance with each principle of this Policy, performance against stated metrics, any reported incidents or complaints, and adherence to legal obligations. For example, an audit checklist would verify that the fairness tests were done and documented, that user opt-outs are respected by the AI, that explanations provided to users were accurate, etc. The results of audits will be reported to senior management and summarized for the Board or oversight authority if required. Any findings of non-compliance or improvement areas must be addressed in a timely manner with a clear action plan.

Audit Trail for Data and Models: Traceability extends to data provenance and model development. HGA will keep an audit trail of data sources for training and input to AI: we record where data came from (e.g., “consultant profile data as of July 2025 snapshot”), under what consent or authorization it was collected, and how it was pre-processed. Likewise, if a model is trained, we keep the training code, random seeds (for reproducibility), and evaluation scripts so that the model training process can be replicated if needed. This is important for transparency and for responding to any challenges (for instance, if a regulatory body questions a particular outcome as potentially biased, we should be able to reproduce the conditions and show how the result happened).

External Audits and Certification: Where relevant, HGA is open to external audits or certification processes. Some clients or donors might request an independent audit of our AI systems for compliance with their standards. We will cooperate and provide auditors with necessary information (under appropriate confidentiality). If industry certifications for AI ethics or AI quality emerge (for example, a seal of compliance with OECD AI Principles, or conformity with forthcoming EU AI Act requirements), HGA will pursue such certifications to validate our commitment.

Use of Audit Findings: Auditability is not merely for show; HGA is committed to using the insights from audits to continuously improve. After each audit/review, responsible teams will convene to discuss the findings and implement recommendations. This could result in updates to the Policy itself, additional training for staff, technical fixes to systems, or in some cases, decommissioning an AI tool that cannot be made compliant. We also ensure that any non-conformance is documented and corrective actions are tracked to completion (see Corrective Actions section).

In summary, auditability and traceability form the backbone of accountability. They allow HGA to verify that our principles are not just words on paper but are in fact being executed in practice. They also position us to be responsive to questions from individuals (e.g., a consultant asking “why wasn’t I selected?” can trigger an internal review using our logs) or inquiries from authorities (e.g., data protection regulators or donor compliance officers auditing our practices). By building systems that are auditable by design, HGA ensures that ethical governance of AI is an ongoing, verifiable process.

User Rights: Contestability and Appeal

Policy Statement: Users of the HGA Digital Platform – including consultants, client organizations, or any individuals subject to AI-informed decisions – have explicit rights to understand and challenge those decisions. HGA upholds the principle that those adversely affected by an AI system’s output should be able to challenge and seek review of the outcome[20]. We have established processes to enable users to exercise their rights to contest decisions, obtain human intervention, and receive timely resolutions. These rights empower users and ensure that AI serves their interests without undermining their autonomy or opportunities.

Right to Be Informed: As described under Transparency, users will be informed when AI plays a role in a decision that affects them. This is the first step in enabling contestability – one must know an AI was involved to decide whether to trust or challenge it. HGA ensures that our communications (whether in-app notifications, emails, or policy notices) clearly state the involvement of AI in decisions like shortlisting for a consultancy, automated profile screening, etc. Additionally, users have the right to request further information about the logic of the decision (the right to explanation as far as applicable). Our Platform provides channels (such as a help center or contact form specifically for AI inquiries) for users to ask, “Why was this decision made about me?” and we will respond with an explanation as described earlier.

Right to Contest and Human Intervention: In accordance with GDPR Article 22 and global best practices, if an individual disagrees with or is negatively impacted by an AI-informed decision, they have the right to contest it and seek human intervention[4]. HGA’s process for this is as follows:

We provide an accessible appeal mechanism on the Platform. For example, if a consultant is not selected for a project primarily due to an AI ranking, the consultant can click “Request Review” or contact our support indicating they wish to appeal the decision.
Upon an appeal, a human reviewer (designated HGA staff or a committee not involved in the initial decision) will re-examine the case. They will review the consultant’s profile, the project requirements, and how the AI arrived at its recommendation. The reviewer has the authority to overturn or adjust the decision if appropriate. Importantly, the human reviewer will do so independently and impartially, considering any additional input the user provides (e.g., “my profile was missing an update that I have since added” or “I believe the AI misunderstood my experience in sector X”). Our policy is that a fresh look will be given, not just a rubber-stamp of the AI’s outcome[21].
The outcome of the human review is communicated to the user with an explanation. If the decision stands, we provide a reason (e.g., “After review, we found that the decision was consistent with the posted criteria. The other candidate had more relevant regional experience.”). If the decision is changed, we explain the new outcome (e.g., “We have added you to the shortlist for further consideration, as we recognized your additional qualifications.”).

No Penalty for Contesting: Users will not be penalized in any way for exercising their right to contest. HGA views feedback and appeals as opportunities to improve our processes. Contesting a decision will not label the user as “troublemaking”; on the contrary, it might highlight a flaw in our AI or data that we need to fix. All HGA staff are trained to handle appeals respectfully and objectively.

Correction of Errors: If a user’s contestation reveals an error in the AI system (for example, the AI was using outdated data, or a bug caused a mis-ranking), HGA will rectify not only the individual case but also address the root cause. The user will be informed of the correction and, if applicable, any broad fix (e.g., “We discovered an issue in our algorithm which we have now corrected to prevent similar occurrences”). Additionally, if the error may have affected others, we will review other decisions and notify relevant parties as appropriate.

Additional User Rights: In conjunction with contestability, users retain all data subject rights provided by law. For instance:
– Access – Users can request access to their personal data that the AI used, to ensure transparency.
– Rectification – Users can correct inaccurate personal data in their profiles which may have led to a suboptimal AI decision. HGA encourages users to keep their information up-to-date and provides easy means to do so.
– Erasure – Users can request deletion of their personal data from our Platform (subject to contractual necessity or legal requirements). If such a request is made, we will also remove or retrain AI models that significantly relied on that individual’s data, as feasible, to honor the spirit of the request (and, at minimum, cease any automated decisions affecting that user).
– Opt-Out – Where possible, HGA may allow users to opt out of certain AI-driven processes. For example, a consultant might choose not to use an AI auto-application tool and instead submit proposals entirely on their own; or an organization might request that their project’s applications be evaluated purely by humans without AI screening. We will accommodate such preferences when practicable, or explain any limitations if manual processes are not available.

User Support and Guidance: We will maintain a user support function that is knowledgeable about this Policy and AI usage. If users have questions about an AI feature or need assistance with an appeal, support staff (or a designated AI ethics officer) will guide them through the process. The goal is to make the exercise of these rights as simple and quick as possible. We aim to resolve most AI-related inquiries or appeals within a reasonable timeframe (e.g., within 10 business days for standard requests, and sooner for urgent matters like active project selection decisions).

Through these measures, HGA ensures that users remain empowered and in control when AI is part of the equation. Contestability and appeal rights prevent AI from ever being a black-box judge of someone’s capabilities or prospects; instead, AI becomes a tool that works for users, with human adjudication available as the final safeguard. Upholding user rights is not only legally required (by laws like GDPR) but is also fundamental to HGA’s client service philosophy and ethical culture. We want all users to have confidence that they are treated fairly and can always voice concerns and have them fairly addressed.

Compliance with Laws and Best Practices

HGA operates across multiple jurisdictions and is committed to complying with all applicable data protection and confidentiality laws, while adopting a highest-standard, jurisdiction-neutral approach. This means HGA and all Users should follow not only the letter of the law in their country, but also the spirit of internationally recognized privacy and security principles.

Global Data Protection Laws: HGA handles personal data of individuals from various countries (consultants, client contacts, etc.), and therefore adheres to key privacy regulations including the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), among others[27]. Even if a particular law (like GDPR or CCPA) may not strictly apply to a given situation due to jurisdiction, HGA’s policy is to voluntarily align with the core principles of those regulations[28][29]. Such principles include lawfulness, fairness, and transparency in processing personal data; purpose limitation (using data only for the purposes collected); data minimization; accuracy; storage limitation; integrity and confidentiality (ensuring security); and accountability. For example, we will provide notice to individuals about how their data is used, obtain consent or have a legitimate basis for processing personal data, allow individuals to access and correct their data, and honor opt-out or deletion requests as described in Section 9.
Cross-Border Data Transfer: By the nature of HGA’s work, personal data may be transferred across international borders (e.g., a consultant in one country may have their CV shared with a client in another country, and stored on cloud servers in a third country). HGA ensures that such transfers comply with applicable transfer laws and mechanisms. Users consent to the international transfer of personal data as needed for HGA’s operations[28], and HGA will use safeguards such as standard contractual clauses or trusted cloud providers to protect data in transit and at rest. If your jurisdiction has data residency requirements, HGA will attempt to accommodate them or will inform you if data will be stored elsewhere. Users handling data should be aware of where they are sending it – do not, for example, email a list of EU citizens’ data to someone in a country with poor data protection without consulting our DPO, as that could violate GDPR’s transfer rules.
Industry Standards and Certifications: In addition to laws, HGA follows industry best practices and standards for information security. For instance, HGA’s handling of payment card information (if any) complies with the Payment Card Industry Data Security Standard (PCI DSS)[30]. We undergo regular security assessments and audits to ensure compliance with such standards[31]. While these certifications and audits are handled by HGA management, Users must do their part by following all security protocols – many standards require staff awareness and compliance.
Client and Donor Requirements: Many of HGA’s clients (such as international development agencies, World Bank, UN, etc.) have their own rules about confidentiality, data protection, and ethics. It is HGA’s policy that we and our consultants comply with any such contractual requirements. For example, if a donor’s policy requires that all project data be kept confidential for 10 years, or that no project information be released without donor consent, those requirements flow down to every User involved. If a client asks a consultant to sign a separate Non-Disclosure Agreement (NDA) to cover their information, the consultant must do so[32] (HGA will inform and coordinate, as needed). Violation of a client’s confidentiality requirements is considered a violation of this Policy. Always familiarize yourself with any specific confidentiality clauses in the contracts or terms of a project you are working on.
Intellectual Property and Copyright: Respect intellectual property laws related to the information you handle. Do not copy or distribute documents in a way that infringes copyrights (for example, don’t take a training manual given under license for a project and reuse it elsewhere without permission). HGA’s standard contracts ensure that deliverables and materials are properly owned or licensed; as a User, you must abide by those terms. If uncertain, ask whether certain materials can be reused or if they need clearance.
Export Controls and Sanctions: Although not common in everyday consulting tasks, be mindful that certain technical data or software could be subject to export control laws (e.g., encryption technology, certain technical schematics, data about sensitive sectors). If you work on a project involving such elements, HGA will advise on any export control licenses or restrictions. Likewise, sanctions laws may prohibit sharing information with certain parties or countries. All Users are expected to comply with any such legal restrictions that HGA communicates (for instance, if told not to email project data to a person in a sanctioned country, that must be heeded).
Ethical Conduct: Compliance goes hand in hand with ethical behavior. In handling information, adhere to professional ethics. For example, avoid conflicts of interest where confidential information from one client might tempt you to assist another competing client. Do not misuse any privileged information (like a client’s internal plans) in ways that could be deemed unethical or illegal. HGA has zero tolerance for activities like bribery or fraud – while those are outside this Policy’s main topic, they often involve misuse of information (e.g., sharing bid information with a competitor in exchange for a kickback is both an ethical and confidentiality breach).
Whistleblowing: If a User needs to report misconduct and that involves sharing information that would otherwise be confidential (for instance, reporting financial wrongdoing to authorities), HGA’s policy is not to impede such legally protected whistleblowing. This Policy is not intended to prevent anyone from reporting legal violations to appropriate government authorities or from cooperating in investigations. However, outside those specific scenarios, confidentiality must be maintained.

Global Data Protection Laws: HGA handles personal data of individuals from various countries (consultants, client contacts, etc.), and therefore adheres to key privacy regulations including the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), among others[27]. Even if a particular law (like GDPR or CCPA) may not strictly apply to a given situation due to jurisdiction, HGA’s policy is to voluntarily align with the core principles of those regulations[28][29]. Such principles include lawfulness, fairness, and transparency in processing personal data; purpose limitation (using data only for the purposes collected); data minimization; accuracy; storage limitation; integrity and confidentiality (ensuring security); and accountability. For example, we will provide notice to individuals about how their data is used, obtain consent or have a legitimate basis for processing personal data, allow individuals to access and correct their data, and honor opt-out or deletion requests as described in Section 9.
Cross-Border Data Transfer: By the nature of HGA’s work, personal data may be transferred across international borders (e.g., a consultant in one country may have their CV shared with a client in another country, and stored on cloud servers in a third country). HGA ensures that such transfers comply with applicable transfer laws and mechanisms. Users consent to the international transfer of personal data as needed for HGA’s operations[28], and HGA will use safeguards such as standard contractual clauses or trusted cloud providers to protect data in transit and at rest. If your jurisdiction has data residency requirements, HGA will attempt to accommodate them or will inform you if data will be stored elsewhere. Users handling data should be aware of where they are sending it – do not, for example, email a list of EU citizens’ data to someone in a country with poor data protection without consulting our DPO, as that could violate GDPR’s transfer rules.
Industry Standards and Certifications: In addition to laws, HGA follows industry best practices and standards for information security. For instance, HGA’s handling of payment card information (if any) complies with the Payment Card Industry Data Security Standard (PCI DSS)[30]. We undergo regular security assessments and audits to ensure compliance with such standards[31]. While these certifications and audits are handled by HGA management, Users must do their part by following all security protocols – many standards require staff awareness and compliance.
Client and Donor Requirements: Many of HGA’s clients (such as international development agencies, World Bank, UN, etc.) have their own rules about confidentiality, data protection, and ethics. It is HGA’s policy that we and our consultants comply with any such contractual requirements. For example, if a donor’s policy requires that all project data be kept confidential for 10 years, or that no project information be released without donor consent, those requirements flow down to every User involved. If a client asks a consultant to sign a separate Non-Disclosure Agreement (NDA) to cover their information, the consultant must do so[32] (HGA will inform and coordinate, as needed). Violation of a client’s confidentiality requirements is considered a violation of this Policy. Always familiarize yourself with any specific confidentiality clauses in the contracts or terms of a project you are working on.
Intellectual Property and Copyright: Respect intellectual property laws related to the information you handle. Do not copy or distribute documents in a way that infringes copyrights (for example, don’t take a training manual given under license for a project and reuse it elsewhere without permission). HGA’s standard contracts ensure that deliverables and materials are properly owned or licensed; as a User, you must abide by those terms. If uncertain, ask whether certain materials can be reused or if they need clearance.
Export Controls and Sanctions: Although not common in everyday consulting tasks, be mindful that certain technical data or software could be subject to export control laws (e.g., encryption technology, certain technical schematics, data about sensitive sectors). If you work on a project involving such elements, HGA will advise on any export control licenses or restrictions. Likewise, sanctions laws may prohibit sharing information with certain parties or countries. All Users are expected to comply with any such legal restrictions that HGA communicates (for instance, if told not to email project data to a person in a sanctioned country, that must be heeded).
Ethical Conduct: Compliance goes hand in hand with ethical behavior. In handling information, adhere to professional ethics. For example, avoid conflicts of interest where confidential information from one client might tempt you to assist another competing client. Do not misuse any privileged information (like a client’s internal plans) in ways that could be deemed unethical or illegal. HGA has zero tolerance for activities like bribery or fraud – while those are outside this Policy’s main topic, they often involve misuse of information (e.g., sharing bid information with a competitor in exchange for a kickback is both an ethical and confidentiality breach).
Whistleblowing: If a User needs to report misconduct and that involves sharing information that would otherwise be confidential (for instance, reporting financial wrongdoing to authorities), HGA’s policy is not to impede such legally protected whistleblowing. This Policy is not intended to prevent anyone from reporting legal violations to appropriate government authorities or from cooperating in investigations. However, outside those specific scenarios, confidentiality must be maintained.

In summary, all Users should treat compliance as a core duty. When you are handling data, ask yourself: are we doing this in a way that respects privacy laws and HGA’s high standards? If unsure, seek guidance. HGA’s commitment to being “jurisdiction-neutral” means we often take the most conservative or protective approach. It is better to be overly cautious than to violate someone’s privacy rights or break a law. By following this Policy, you will inherently be following the applicable laws and best practices, as it has been designed to encompass them[29]. Non-compliance not only risks legal penalties for HGA, but can also result in personal liability for individuals in some cases (for example, certain privacy laws have fines for responsible persons). Thus, adherence is in everyone’s interest.

Roles and Responsibilities

Effective implementation of this Policy requires clear definition of responsibilities across the various roles interacting with the HGA Digital Platform. The following outlines the duties of key stakeholder groups and specific roles in upholding AI ethics and responsible use. All individuals, regardless of role, are expected to familiarize themselves with this Policy and act in compliance, but certain roles carry additional, specific obligations as described below.

General Responsibilities of All Platform Users

Compliance and Ethics: Every user (internal staff, consultants, client representatives, etc.) must act in accordance with the principles of this Policy. Users should not attempt to misuse or manipulate AI systems for unethical advantage. They are expected to report any issues (bias, errors, security concerns) they observe in AI outputs or behavior.
Data Accuracy: Users have a responsibility to provide accurate and truthful information on the Platform. Since AI tools may use this information (e.g., consultant profiles, project descriptions), accuracy helps ensure fair and correct AI outcomes. Submitting false or misleading data not only violates Platform terms but can lead to biased or harmful AI results.
Privacy Respect: Users must respect the privacy of others when inputting or handling data. For example, a client posting a project should not upload unnecessary personal data about individuals, and consultants should handle any data they access (like peer reviews) in line with confidentiality rules. Users should also honor any confidentiality of AI-driven content if so designated (e.g., not publicly disclosing proprietary AI recommendations or code they might access).

HGA Senior Management

Tone at the Top: HGA’s leadership (executives and directors) is responsible for fostering a culture of ethical AI use. Management shall endorse this Policy and allocate necessary resources (budget, personnel, training) to implement it effectively.
Oversight: Senior management will receive periodic reports on AI system performance and compliance (e.g., summaries of audit findings, incident reports). They are responsible for reviewing these and ensuring that any strategic decisions take into account AI ethics (for instance, approving the launch of a new AI feature only after confirming it has passed ethical review).
Accountability: Leadership ensures that there are clear lines of accountability (as detailed in this section) and that those in charge of AI governance have the authority to enforce compliance. Executives will intervene if there are systemic issues, and have ultimate responsibility for enforcement actions, including approving sanctions for non-compliance when necessary.

System Manager (and Technical Development Team)

Role: The System Manager is the individual (or team) in charge of the technical management of the HGA Digital Platform, including its AI components. This role might encompass product managers, lead developers, or an appointed AI Ethics Officer if one exists.

Responsibilities:
– AI Development & Maintenance: Ensure that all AI systems are developed in line with the principles of this Policy. This means incorporating checks for fairness, privacy, security, etc., during development. The System Manager must validate that requirements (e.g., bias mitigation, documentation, testing) are met before approving an AI system for deployment.
– Documentation & Traceability: Maintain the comprehensive documentation and logs for AI systems as described in the Auditability section. The System Manager must see that models, data, and decisions are traceable. They coordinate periodic reviews of this documentation for completeness and accuracy.
– Monitoring & Quality Control: Continuously monitor AI outputs in production for any anomalies or ethical concerns. The System Manager should use dashboards or reports to track key indicators (such as demographic distribution of AI-driven recommendations as a fairness check, or error rates as a performance check). If monitoring reveals issues, the System Manager triggers an investigation and fixes (e.g., retraining a model, adjusting thresholds, or rolling back to a previous model version).
– Incident Response: In case of any AI-related incident (bias complaint, data breach, malfunction), the System Manager leads the technical investigation to identify the root cause. They work closely with the compliance team to report findings and implement technical corrective measures. For example, if an AI matching algorithm is found to systematically exclude candidates from a particular region, the System Manager would analyze why (perhaps the training data was imbalanced) and apply a remedy (such as updating the model or adding data).
– Liaison with Oversight Bodies: The System Manager serves as a point of contact for internal or external audits regarding AI. They should cooperate with auditors, providing data and explanations as needed. If an AI Ethics Committee or Officer exists, the System Manager regularly briefs them on system status and issues.
– Training & Guidance: The System Manager should also help educate other HGA team members about the technical aspects of AI and how to interpret AI outputs. They may produce internal guidelines or tools to help Business Developers or Consultants understand how to work with the AI (e.g., explaining confidence scores or the meaning of flags the AI might raise).

Business Developers (and Project Managers) – Internal HGA Role

Role: Business Developers in HGA are those who engage with clients (donors, organizations), help scope projects, and often oversee the matching of consultants to projects. They act as intermediaries between the consultants and the clients on the Platform, and likely use the Platform’s AI features to facilitate their work.

Responsibilities:
– Ethical Use of AI in Selection: When using AI recommendations or rankings for consultants, Business Developers must apply them fairly and judiciously. They should treat the AI as a support tool, not an infallible judge. This means reviewing AI outputs critically: if the AI’s top-ranked consultant seems off-base (e.g., missing an obvious candidate), they must investigate rather than blindly accept it.
– Avoiding Bias: Business Developers should be aware of their own biases and ensure they do not reinforce any bias from AI. For instance, if an AI output appears biased, they should counteract it by giving additional consideration to those who might have been under-ranked. They should also provide feedback to the System Manager about any suspected bias so the model can be improved.
– Transparency to Clients: In communications with client organizations, Business Developers will uphold transparency about AI use. If clients ask how consultants were shortlisted, the Business Developer can explain that an AI tool was used as an initial screen along with human judgment, and highlight the criteria used. They must not misrepresent an AI-driven decision as purely human, nor vice versa. Honesty in how matches are made is part of maintaining trust with clients.
– Protect Data: Business Developers often handle sensitive data (project requirements, consultant info). They should adhere to privacy principles – e.g., only input necessary data into the Platform/AI, secure any reports or outputs generated by AI, and not export or email AI data in insecure ways. If they create any local copies of AI outputs for analysis, those must be protected.
– Client & Consultant Queries: As frontline contacts, Business Developers might receive questions or challenges from consultants (“Why wasn’t I selected?”) or clients (“Did we get the best candidates?”). They are responsible for responding in line with this Policy: providing explanations (with support from System Manager if needed) and informing them of their rights (like the consultant’s right to appeal a decision). Business Developers should never ignore or dismiss such queries – they should route them through proper channels (e.g., suggest the consultant formally appeal via the platform, or escalate complex issues to an ethics officer).
– Compliance with Donor Guidelines: Since Business Developers deal directly with project opportunities that may be donor-funded, they must ensure that all processes – including AI-assisted ones – meet donor requirements. As noted, World Bank and similar donors require fairness and transparency in consultant selection[8]. Business Developers must confirm that any AI usage does not conflict with these (for example, if a donor requires that all eligible consultants be considered, the Business Developer should ensure the AI isn’t inadvertently screening someone out improperly). If needed, they should be prepared to share information about the selection process with donor auditors, with support from HGA compliance.

Consultants (Independent Contractors on Platform) – External Role

Role: Consultants are the professionals who use the Platform to find and undertake consulting assignments through HGA. They are not employees, but their adherence to certain rules is critical as they interface with AI tools for their own profiles and proposals.

Responsibilities:
– Honest Profile and AI Inputs: Consultants must provide truthful and accurate information in their CVs, profiles, and any answers to AI-driven questionnaires. Lying to an AI (e.g., inflating experience hoping the AI ranks them higher) is a breach of both ethics and contract. If using an AI assistant to create content (like a cover letter), they should verify the content’s accuracy (no fabrications about credentials or experience).
– Use AI Tools Responsibly: The Platform may offer AI tools to consultants (such as an “AI Agent” to draft applications). Consultants are responsible for reviewing and editing AI-generated suggestions. They should not blindly submit AI-written text without ensuring it is correct and reflective of their voice. They are also encouraged to provide feedback on these tools – if an AI suggestion seems irrelevant or inappropriate, they should report it so HGA can improve the system.
– Confidentiality and Data Handling: If consultants receive any data through AI insights (for example, the platform might use AI to analyze a project’s requirements and give all applicants some insights), they should treat that data as confidential. Also, they should not attempt to reverse-engineer or exploit the AI system in a way that violates fairness (e.g., trying to find out how to “game” the AI scoring beyond simply improving their legitimate qualifications). Any attempt to tamper with the AI (such as inputting fake data or sharing accounts to boost scores) is prohibited.
– Ethical Conduct: Consultants, per their contract with HGA, must observe the highest ethical standards[3]. This extends to AI interactions. For example, if a consultant becomes aware of a bug that gives them an unfair advantage (like seeing other candidates’ private info via AI), they are obligated to report it and not exploit it. Similarly, consultants should avoid any fraudulent behavior in connection with AI processes (the contract explicitly forbids fraudulent, collusive practices[22], which would include any scheme to manipulate algorithmic outcomes).

Client Organizations (External Role)

Role: Client organizations (such as international development agencies, NGOs, companies) use the Platform to post consulting opportunities and select consultants.

Responsibilities:
– Fair Opportunity Posting: Clients should formulate project listings and criteria in a fair, non-discriminatory manner. For instance, they should not request the AI or HGA staff to exclude candidates on bases that violate non-discrimination (e.g., “only candidates under 40” would be inappropriate). HGA will refuse any client request that conflicts with our ethics (and our agreements likely stipulate this).
– Participation in Ethical AI Use: Clients are encouraged to engage with the Platform’s AI outputs transparently. If a client has access to AI-shortlisted candidates, they should treat all candidates fairly in their final selection and are expected to respect the integrity of the process. We also expect that clients will keep any AI-provided insights confidential and use them solely for the intended purpose of evaluating candidates for that specific project.
– Feedback: Clients can provide valuable feedback on the quality and fairness of AI matches. We invite them to notify HGA if they believe a qualified consultant was overlooked or if a recommendation was off-target. Such feedback will help us refine the AI (and possibly reveal biases we need to address).
– Compliance: Many client organizations (especially multilateral institutions) have their own ethical guidelines. By using our Platform, they agree not to impose or request actions that would cause HGA or our consultants to violate this Policy or any law. If a client’s internal AI or data requirements are stricter (for example, a UN agency might have rules on data usage), HGA will coordinate to meet those as well, but clients should communicate any such needs.

Receivables/Payables Officers and Other Internal Staff

Role: These are HGA internal roles focused on financial transactions, contracting, and administrative support within the Platform. They may not directly interact with AI for decision-making about consultants, but they might use AI for tasks like invoice processing, forecasting, or risk flagging.

Responsibilities:
– Use of AI in Administrative Tasks: If any AI is used in financial or admin processes (e.g., an AI tool to flag unusual invoices or to predict project budgets), these staff should use them as aids and double-check their outputs. They remain responsible for financial accuracy and compliance (the AI might warn of a potential error, but the officer must verify it).
– Privacy and Security: Handling personal and financial data means these officers must adhere strictly to data protection. If an AI processes payment data or personal info for compliance checks (e.g., anti-fraud AI scanning transactions), officers must ensure that the data fed into such AI is correct and that outputs (like a fraud alert) are handled discreetly and lawfully. Any personal data in financial records is protected under GDPR/CCPA as well.
– Reporting Issues: If, in their processes, they notice anomalies from AI tools (like false positives in fraud detection or system errors), they should report to the System Manager and not assume the AI is always right. They should also communicate with consultants or clients if an AI-driven financial decision affects them (for example, if an automated system puts a payment on hold due to suspected risk, the officer should inform the affected party and investigate promptly, not just wait passively).

Summary of Role Responsibilities: (for clarity, we present a brief recap in list form)
– System Manager: Ensure ethical design, monitoring, and maintenance of AI; address technical issues; maintain documentation; lead AI incident response.
– Business Developer: Use AI outputs responsibly in consultant selection; provide human oversight; ensure fairness and transparency to consultants and clients; report AI issues.
– Consultant: Provide honest data; responsibly use AI tools; review AI-generated content; uphold ethical standards and confidentiality.
– Client Organization: Post fair requirements; respect process outcomes; use AI-driven insights properly; give feedback; honor ethical and legal standards.
– All HGA Staff: Comply with Policy; attend training; report violations or concerns; cooperate in audits and improvements.

HGA will periodically review and update role definitions as our Platform evolves. New roles (such as an AI Ethics Officer or Data Protection Officer) may be introduced, and their responsibilities will be integrated into this Policy accordingly. The key principle is that ethical AI is a shared responsibility – everyone involved has a part to play in ensuring the technology is used for good and in line with our values.

Implementation Timeline and Review

HGA recognizes that implementing this Policy effectively requires a structured plan and regular review. We commit to a concrete timeline for rolling out the necessary measures, training, and system updates, as well as establishing an ongoing cycle of reviews and improvements. Below is the implementation roadmap and review schedule:

Policy Adoption (Immediate): This Policy becomes effective as of the date approved by HGA leadership. Upon adoption, it will be circulated to all current HGA employees, consultants, and relevant stakeholders. The Policy will also be made available via the HGA Digital Platform (e.g., in the user portal or help section) for easy reference by all users.
Training and Awareness (Within 30 days of Adoption): HGA will conduct mandatory training sessions for all internal staff on the contents of this Policy and their responsibilities. Specialized training will be provided based on role: for example, technical workshops for System Managers and developers on how to perform bias testing and ensure transparency, and separate seminars for Business Developers on fair use of AI in recruitment/selection. We will also provide an orientation or briefing to our active consultants (perhaps via a webinar or an online module) explaining the new Policy, especially focusing on how it benefits them (fairness, appeal rights) and their duties (truthful data, etc.). All new hires or new platform users will receive this training as part of onboarding.
Initial AI Systems Audit (Within 60 days): The System Manager, in collaboration with an internal audit or compliance officer, will perform a thorough audit of all existing AI systems on the Platform to gauge current compliance with the Policy. This includes evaluating existing models for bias, checking logs and documentation, and ensuring needed explanations can be generated. The audit will produce a report identifying any gaps or compliance issues. For example, if an existing AI tool lacks proper documentation or if a potential bias is found in historical data, these will be noted.
Remediation of Legacy Issues (Within 90 days): Based on the initial audit findings, HGA will remediate any issues in current AI systems. This may involve retraining models with more diverse data, enhancing security measures, writing missing documentation, or modifying features that don’t meet the new standards. A timeline for each remediation item will be drawn (some fixes might be immediate, others might require phased implementation). By the 90-day mark, all critical issues (those that pose high ethical or legal risks) will be addressed. Lower-risk improvements may continue beyond 90 days but will be tracked to completion.
Policy Integration into Development Lifecycle (Immediate and Ongoing): Effective immediately, all new AI projects or features will be subject to this Policy. HGA will update its development process checklists to include ethical review gates – for instance, before an AI feature goes live, the product team must fill out a compliance checklist confirming fairness testing, security checks, etc., consistent with this Policy. This ensures that from day one of development, the principles are integrated (sometimes referred to as “Ethics by Design”).
Stakeholder Communication (Within 30 days): HGA will formally communicate to client organizations and partners about our AI Ethics Policy. This may be via email newsletters, updates in contracts or MOUs, or direct meetings. The purpose is to assure them of our commitment (perhaps highlighting that we align with UNESCO and OECD principles) and to let them know what changes, if any, they might experience (for example, new notices on the platform, or being asked to comply with certain guidelines when using the platform). We will also invite their questions or input.
Periodic Review (Every 6 months initially, then annually): For the first year of implementation, HGA will conduct semi-annual reviews (every 6 months) of the Policy’s effectiveness and the state of AI ethics on the Platform. This involves reconvening the relevant team (System Manager, compliance officer, business reps) to discuss: any incidents that occurred, feedback from users, results of any audits or monitoring, and changes in the external environment (new laws or guidelines). The Policy will be updated if needed (e.g., if GDPR or other laws change, or if we find a principle needs refinement). After the initial year and once the program is stable, we will move to an annual review cycle. However, any major event (like a significant breach or a major new AI feature) will trigger an out-of-cycle review to ensure the Policy remains up-to-date and adequate.
External Benchmarks and Certifications (Within 1 year): HGA aims to benchmark our AI ethics program against industry standards. Within the first year, we will explore external certifications or compliance checks – for example, if the emerging EU AI Act or other regulation comes into force, we will ensure readiness to comply by its effective date. We will also consider participating in initiatives or forums on AI ethics to stay current with best practices.

Milestones Table (Summary):
– Day 0: Policy approved and published.
– Day 0-30: Dissemination and training for internal staff and consultants.
– By Day 60: Complete baseline audit of AI systems for compliance.
– By Day 90: Remediate high-priority issues from audit; interim compliance report to management.
– Ongoing: Embed ethics checks in development; handle issues as they arise.
– Month 6: First semi-annual review; adjust Policy or practices as needed.
– Month 12: Annual comprehensive review; consider external audit/certification; report to Board or equivalent governing body on AI ethics status. Repeat annually thereafter (or more often if needed).

HGA’s timeline demonstrates that this Policy is not a one-off document but the start of an evolving program. We understand that building responsible AI is an ongoing process of improvement. By setting these concrete deadlines and review mechanisms, we hold ourselves accountable to making the principles real in practice and sustaining that into the future.

Reporting and Documentation

An essential aspect of enforcing this Policy is establishing clear protocols for reporting issues and maintaining documentation of compliance efforts. HGA encourages a transparent, blame-free environment for raising concerns related to AI ethics or compliance. At the same time, we impose strict documentation duties on ourselves to ensure we can demonstrate what we have done to uphold this Policy. The following outlines how reporting and documentation are managed:

Incident Reporting (Internal):
– Whistleblower Protection: Any HGA employee or contractor who observes what they suspect to be a violation of this Policy, unethical AI behavior, or a security/privacy incident is required to report it promptly to management (e.g., to their supervisor, the System Manager, or a designated compliance officer). HGA maintains a whistleblower-friendly policy – reports can be made confidentially or even anonymously (via a hotline or secure form), and the reporter will be protected from retaliation. The focus is on resolving the issue, not blaming the reporter.
– Reporting Channels: We will set up specific channels for AI-related issues. This might include a dedicated email address (e.g., ethics@humanicsgroup.org) or an online incident submission form on the company intranet. For urgent matters (like a potential data breach or a severe discriminatory outcome currently unfolding), we also provide phone contacts for immediate escalation. All staff will be informed of how to use these channels during training.
– Response to Reports: Upon receiving a report, HGA will acknowledge it and initiate an investigation within a defined timeframe (e.g., 5 business days for normal issues, 24 hours for critical ones). A small investigation team will be assigned appropriate to the issue – including, for example, a technical lead for system issues, HR for any staff misconduct angle, and legal counsel if regulatory implications exist. They will gather facts (review logs, interview people, etc.). The outcome of the investigation will be documented and communicated to relevant leadership, and to the reporter if appropriate (some results might be confidential, but we aim to give feedback like “your concern was valid and we have taken XYZ steps” or “after investigation, the system was found to be functioning correctly, here’s why”).

User Reporting (External):
– User Helpdesk: For platform users (consultants, clients), we integrate AI-related issue reporting into our helpdesk/customer support structure. If a user encounters what they think is an AI error or bias – for example, “The platform’s AI translation produced inappropriate language” or “I suspect the ranking algorithm overlooked my qualifications” – they can contact support through the app or email. Support staff are trained to recognize when a ticket involves an AI ethics issue and escalate it to the appropriate specialist (System Manager or ethics officer).
– Transparency and Resolution: We will treat user-reported issues seriously and aim to resolve them to the user’s satisfaction when possible. Even if the issue is a misunderstanding, we take the time to explain how the AI works or why a certain outcome happened, as part of our commitment to transparency. If the user has revealed a genuine flaw or bias, we will apologize and fix it, possibly re-running a decision process if feasible (e.g., reconsidering a consultant’s application after fixing a bug).

Documentation Requirements:
– Policy Compliance Records: HGA will maintain records proving compliance with each aspect of this Policy. This includes training attendance logs (to show who has been trained and when), completed checklists for AI system reviews, DPIA reports if done, bias testing results, and audit reports. These documents may be requested by clients or regulators, so we organize and store them systematically (likely in our compliance department’s repository with appropriate confidentiality).
– Decision Logs: As noted in Auditability, logs of AI decisions and interventions form part of documentation. For any contested decision, we will keep a record of the appeal, the review process, and the final resolution. This not only ensures accountability but can serve as evidence if later a question arises (for instance, if a participant claims they were unfairly treated, we have the logs to analyze the case).
– Incident Reports: For every significant incident (security breach, confirmed bias event, etc.), an official incident report will be written. The report will outline incident description, impact analysis (whom/what was affected), root cause, and corrective actions taken. These reports are reviewed by senior management and kept on file. If required by law or contracts, some incidents may also be reported externally (see Breach Management below).
– Meeting Minutes: The proceedings of key oversight meetings – such as the semi-annual or annual AI ethics review meetings, or any AI Ethics Committee meetings – will be minuted. Decisions made (e.g., to update a policy, to invest in a new tool, or to escalate an issue to the board) will be recorded. This provides a paper trail of our governance in action.
– Regulatory Documentation: If subject to any regulatory scheme (for example, if certain AI systems fall under forthcoming EU AI Act classification), we will prepare and maintain required documentation, such as conformity assessments or technical dossiers. We also document any communications with data protection authorities or other regulators (e.g., if we sought advice or notified them of something) to show proactive compliance.
– Retention of Documentation: All documentation will be retained for a minimum period, typically consistent with legal requirements or business needs. For example, GDPR-related documents (like DPIAs) should be kept as long as the processing continues, and then some years after. Incident reports might be kept for several years for reference. HGA will define retention schedules aligning with laws (such as keeping records for at least 5 years for compliance evidence, unless laws dictate longer).

Continuous Improvement: The act of reporting and documenting is not just bureaucratic formality; HGA uses these processes to learn and improve. Trends in incident reports might indicate a systemic issue needing attention (e.g., multiple similar user complaints could spark a redesign of an AI feature). Documentation reviews might reveal gaps in our policies or training (e.g., if many people report not understanding how to appeal, maybe our communication is lacking). We integrate these lessons into updates of this Policy and our practices.

In conclusion, through robust reporting channels and thorough documentation, HGA ensures visibility into the functioning of our AI governance. This openness allows us to catch problems early, address them transparently, and maintain accountability to all stakeholders about how our AI systems are managed. It also builds confidence – internally and externally – that if something goes wrong, there is a reliable mechanism to track it and make it right.

Breach Management and Corrective Actions

While HGA strives to prevent any violations of this Policy or lapses in AI system performance, we must be prepared to act decisively if they occur. “Breach” in this context may refer to various scenarios: a data breach (unauthorized access or loss of personal data), a policy breach (non-compliance with the AI ethics standards set out here), or a security breach of the AI system’s integrity. This section details how HGA manages such incidents and the steps for remediation and prevention of recurrence.

Breach Identification:
– A breach can be identified through our monitoring systems, internal or external audits, user or staff reports, or alerts (for example, an intrusion detection system flagging irregular activity). The first step upon identification is containment: ensure the breach is not ongoing (e.g., cut off unauthorized access, halt a malfunctioning AI process, etc.). The System Manager and IT security team will lead the containment for technical breaches, while the compliance team may lead for procedural/policy breaches.

Notification and Escalation:
– Internal escalation happens immediately. Relevant department heads and senior management are informed through an incident notification. If the breach involves personal data and meets the threshold of a reportable incident under GDPR or other laws, HGA will notify the appropriate supervisory authority (such as an EU Data Protection Authority) within 72 hours of awareness, as required by GDPR, and document the reasons for any delay beyond 72 hours[23]. If the breach could impact individuals (e.g., their personal data was compromised or a decision error could have harmed them), we will also notify those individuals without undue delay, providing them with information about the nature of the breach and any steps they should take (as mandated by law). For example, if a security breach leaked consultant personal information, those consultants would be informed and perhaps advised to take precautions like changing passwords.
– If the breach pertains to donor-funded work (e.g., an ethical violation on a World Bank project), we will also inform the donor if contractually required or appropriate, aligning with obligations to report fraud, corruption, or significant issues. HGA’s Consultant Guidelines clause in contracts requires disclosure of conflicts or investigations[24], so similarly we would disclose major incidents affecting a donor project’s integrity.

Investigation:
– HGA will form an incident response team to investigate the breach thoroughly. The team typically includes: System Manager/technical experts (to analyze technical causes), compliance/legal (to assess legal impact, e.g., GDPR obligations), and business leadership (to evaluate client impact). The investigation will determine: What happened? How did it happen? Who or what was responsible? What data or outcomes were affected? For example, in a data breach, we identify what data was accessed and how (hacked account, software vulnerability, etc.). In an ethics breach (like an AI system found to be discriminatory), we determine how that bias slipped through (was it in data, or did someone bypass testing?).
– The results of the investigation are documented in an incident report (as mentioned in Reporting section) and include a root cause analysis. We also assess the impact severity (low, medium, high) to prioritize response. A high-severity breach (e.g., large-scale personal data leak or a systematic unfair hiring practice) gets immediate attention from top management and possibly Board oversight.

Corrective Actions:
Based on investigation findings, HGA implements corrective measures, which can be grouped as follows:
– Technical Fixes: These address flaws in the AI system or security. They might include patching software, improving encryption, restoring a system from clean backup, retraining a model with corrected data, or adding new data filters. For instance, if a breach was due to a software bug, we fix the bug and test extensively to ensure the vulnerability is closed. If an AI produced biased results, we may adjust its algorithm, include more representative data, or impose fairness constraints in the model. In some cases, we might disable a feature entirely until a more robust solution is developed.
– Process Improvements: We examine whether our processes failed. Perhaps a step was skipped (e.g., a bias check was not done due to time pressure) or a human oversight step didn’t catch an issue. We will reinforce or modify processes – this could mean updating the development checklist, introducing an extra review stage, or enhancing the audit frequency. We might also tighten access controls or change configuration management if the breach was due to improper access or change to the system.
– Personnel Actions: If the breach involved misconduct or negligence by individuals, HGA will take appropriate action. This can range from retraining and coaching to disciplinary measures (warnings, suspension, or termination in severe cases). For example, if an employee willfully ignored policy (say, intentionally deployed an AI model without required approval), they would face consequences. Our approach is corrective rather than punitive, but willful or repeated violations may result in termination, especially if they jeopardize legal compliance or company reputation.
– User Remedies: When users have been adversely affected, we provide remedies where possible. For data breaches, this might include offering credit monitoring to affected individuals, or other support as appropriate. For decision-related issues, a remedy could be re-running a selection process fairly, or offering the affected consultant an opportunity for a different project if feasible. While such remedies may not erase the issue, they show good faith effort to make things right and mitigate harm.
– Communication and Transparency: After addressing the immediate issues, HGA will communicate with relevant stakeholders about what happened and what we did about it. Internally, we share lessons learned through perhaps a post-mortem meeting or memo (without unduly pointing fingers, focusing on improvement). Externally, if the incident was public or known to clients, we may release a statement or report explaining the steps taken. Transparency in aftermath helps rebuild trust.

Follow-up and Review:
After corrective actions, HGA will monitor the situation closely. For example, if a model was retrained due to bias, its outputs will be reviewed in subsequent cycles to ensure the bias is indeed gone and not creeping back. We may also schedule a special follow-up audit focusing on the breached area (maybe 3 months after, to verify that all recommended fixes have been implemented and are effective). The findings from the breach and its handling will feed into the next Policy review – perhaps prompting new provisions or stronger controls to prevent a recurrence.

Legal Consequences:
HGA acknowledges that certain breaches, especially involving personal data, have legal consequences (fines, penalties). Our approach is to fully cooperate with regulators, take responsibility, and rectify issues to potentially mitigate penalties. Our thorough documentation of compliance efforts and prompt action can serve as evidence of due diligence, possibly reducing liability. Nonetheless, enforcement action by authorities will be respected and complied with. If a breach triggers legal claims from individuals, HGA will address those through appropriate legal channels, again emphasizing our remedial measures and commitment to fairness.

In summary, while our goal is zero incidents, we prepare for the worst to minimize damage and learn from mistakes. Breach management is where our ethical principles are tested under pressure – by responding swiftly, openly, and effectively, HGA aims to maintain trust even when things go wrong. Our clients and users should feel confident that if a problem arises, HGA will tackle it head-on and emerge with stronger systems and safeguards.

Enforcement and Compliance

This Policy is a binding directive for all HGA operations related to AI, and compliance is mandatory. Enforcement mechanisms ensure that the Policy is not just words, but is actively adhered to, with consequences for violations. Additionally, this section ties our Policy commitments back to our legal obligations and contractual duties, reinforcing that compliance is both an ethical stance and a matter of law.

Enforcement within HGA (Employees and Contractors):
– Incorporation into HR Policies: HGA will incorporate compliance with the AI Ethics and Responsible AI Use Policy into our code of conduct and employment conditions. This means each employee has a duty, as part of their job description, to follow the Policy’s guidelines relevant to their role. Any deliberate or negligent breach of this Policy by an employee may be treated as a disciplinary offense. For example, if a developer knowingly deploys an algorithm that they suspect is biased without disclosure, that is a serious breach.
– Disciplinary Process: Enforcement actions for staff can include verbal or written warnings, mandatory re-training, suspension of access to certain systems, and in severe or repeated cases, termination of employment or contract. The severity of action will correspond to factors like: Was the violation willful or accidental? Did it result in harm? Was it self-reported or attempted to be concealed? Our disciplinary procedures (as outlined in employee handbooks) will be followed, ensuring fairness and an opportunity for the individual to explain their case. A committee including HR, legal, and a senior manager may review major cases to decide the outcome.
– Performance Evaluations: To encourage compliance, HGA will make adherence to ethical and compliance standards a factor in performance reviews for relevant roles. For instance, a System Manager might have an objective related to maintaining zero significant compliance incidents, or a Business Developer might be evaluated on feedback from clients/consultants about fairness and transparency. This aligns incentives with Policy goals.

Enforcement with Platform Users (Consultants and Clients):
– Terms of Service Binding: The principles of this Policy will be reflected in the Platform’s Terms of Service or user agreements. By using the Platform, consultants and client organizations agree to comply with the applicable portions of this Policy (e.g., providing truthful data, not engaging in prohibited conduct, respecting privacy). Non-compliance can thus be a breach of contract.
– Account Actions: If a consultant or organization violates the ethical guidelines (for example, a consultant tries to hack the AI system or a client pressures HGA to break fairness rules), HGA reserves the right to take action on their accounts. This could include warnings, temporary suspension from the Platform, or permanent account termination in egregious cases. We would typically warn and educate first – e.g., if a consultant uses inappropriate content, we’d ask them to correct it – but serious violations (like proven fraud or data abuse) could lead to immediate suspension.
– Contractual Remedies: HGA’s contracts (like the Consultant Representation Agreement[25] and project agreements with clients) have clauses requiring ethical conduct and compliance with donor rules. If those are breached, contractual remedies apply. For consultants, HGA might terminate their contract for cause (which is severe but possible if they, say, engage in corrupt behavior on a project). For clients, if a client’s actions force an ethical breach, HGA might withdraw from the project or require the client to remedy the situation (though in practice, we aim to resolve issues cooperatively). The World Bank Consultant Guidelines, for instance, allow termination if a consultant is found to violate anti-fraud provisions[22]; HGA would enforce similar stances to remain eligible for donor-funded projects.
– Legal Action: In cases where a user’s violation of this Policy also violates law (for example, a user stealing data or engaging in harassment via AI tools), HGA will not hesitate to involve law enforcement or pursue legal action to protect our platform and other users. This is of course a last resort, and any such action would follow due legal process.

Alignment with Legal Obligations:
– GDPR and Data Protection: As previously emphasized, HGA complies with GDPR and other privacy laws. Non-compliance with this Policy could result in legal non-compliance (e.g., failing to honor a user’s contestation right could violate GDPR Art. 22, or a data breach mishandled could violate breach notification rules). HGA’s Data Protection Officer (or person fulfilling that role) will ensure that our enforcement of this Policy dovetails with data protection compliance. For instance, if an employee breaches data protection via an AI misuse, the enforcement action must be documented as part of demonstrating accountability under GDPR[26]. We also maintain records of processing and DPIAs as required, and we would stop any AI processing that is found unlawful until it can be brought into compliance.
– CCPA and Consumer Rights: For U.S. operations, particularly if dealing with California residents, we uphold CCPA rights. Compliance means if a user opts out of data sale or requests deletion, our AI systems won’t use their data beyond what’s allowed. Enforcement here is about internal compliance – ensuring our systems and staff respect those requests. Failure to do so can result in regulatory penalties and lawsuits. Thus, our technical enforcement includes building mechanisms to honor opt-outs and our administrative enforcement means disciplining any staff who ignore such requests.
– Donor and Industry Regulations: HGA frequently works with entities like the World Bank, UN, etc. These often have their own compliance frameworks (anti-corruption, procurement integrity). We explicitly commit (in Section 3.2 of our consultant contract) to abide by World Bank Consultant Guidelines[27], including ethics and conflict of interest rules. Enforcement in this domain means if a consultant or staff violates donor ethics (e.g., engages in collusion, or manipulates an AI system to favor a certain outcome for personal gain), HGA will enforce not just our policy but also potentially report the individual to the donor per those guidelines. The World Bank or others can sanction individuals (debarment) – HGA will cooperate with such processes and possibly preempt them by taking our own action first.
– Regulatory Compliance: Should there be new laws like the EU AI Act, or if our business expands to jurisdictions with AI-specific regulations, HGA will incorporate those requirements. Enforcement might include undergoing required conformity assessments, registering certain AI systems with regulators, or ceasing use of any AI deemed unacceptable (like a prohibited use case). Our commitment is that we will not knowingly operate any AI in violation of applicable law. If a law imposes penalties for certain AI behavior, we treat avoidance of those penalties as a compliance priority in line with this Policy.

Auditing Enforcement:
– As part of our internal audits and annual reviews, we will evaluate not just the AI systems, but also how well enforcement of this Policy is working. Are people reporting issues without fear? Are disciplinary actions consistent and fair? We might include metrics like number of incidents reported, time to resolution, etc., to gauge effectiveness. If we find gaps (e.g., people aren’t reporting known issues due to fear or ignorance), we’ll improve training and culture. If we find our enforcement is too lax or too harsh, we will adjust guidelines to managers.

Conclusion of Enforcement Section:
HGA’s stance is that ethical AI governance is non-negotiable. We are ready to enforce these rules firmly because the stakes are high – user trust, legal compliance, and our reputation depend on it. However, enforcement is balanced with fairness; our goal is to educate and correct more than punish. Ultimately, by clearly linking this Policy to everyone’s duties and backing it with consequences, we ensure that it is taken seriously at every level. This closes the loop of our governance program: from high-level principles down to day-to-day actions and, when needed, sanctions, to maintain the integrity of our AI-enabled services.

References and Framework Alignment (Informative)

(The following sources and frameworks have informed the development of this Policy. They are not additional requirements but illustrate HGA’s alignment with global best practices in AI ethics and compliance.)

UNESCO, Recommendation on the Ethics of Artificial Intelligence (2021) – UNESCO’s first global standard-setting instrument on AI ethics, emphasizing human rights, fairness, transparency, accountability, and promoting “fundamental principles such as transparency and fairness” with the “importance of human oversight of AI systems”[1]. HGA’s Policy draws on UNESCO’s values and its policy action areas, aiming to translate those into our organizational context.
OECD, OECD Principles on Artificial Intelligence (2019) – an intergovernmental framework of five values-based principles (inclusive growth, human-centered values, transparency, robustness, accountability) and recommendations for trustworthy AI. HGA particularly echoes the OECD’s calls for transparency (“AI actors should commit to transparency and responsible disclosure”[10]), fairness and non-discrimination (“respect for… equality, diversity, fairness, social justice”[7]), robustness and security (“AI systems should be robust, secure and safe throughout their lifecycle”[18]), and accountability (“AI actors should be accountable for the proper functioning of AI systems”[13]). Our internal controls and accountability structures are built to mirror these guidelines.
GDPR, EU General Data Protection Regulation (2016) – Legal requirements on personal data processing, including provisions on automated decision-making and profiling. Article 22 GDPR and related Recitals establish rights to not be subject to solely automated decisions and to seek human intervention, which HGA fully incorporates (users can obtain human intervention, express their point of view, and contest automated decisions[4]). We also uphold GDPR principles in data handling and breach notification duties[23], ensuring our AI practices meet the strictest data protection standards.
CCPA/CPRA, California Consumer Privacy Act (2018) and CPRA (2020) – U.S. state law influencing data privacy and automated decision transparency. HGA’s commitments to allow opt-outs, provide data transparency, and safeguard personal information are in line with these consumer rights laws.
World Bank, Procurement Regulations & Consultant Guidelines – We adhere to donor guidelines such as those from the World Bank that demand fairness, transparency, and integrity in consultant selection. For example, the World Bank’s guidelines note that “Fairness and transparency in the selection process require that Consultants…do not derive a competitive advantage” over others[8], and that consultants must observe the “highest standard of ethics”[3]. HGA’s Policy operationalizes these principles in our AI-mediated processes to ensure we remain eligible and in good standing for donor-funded contracts.
Industry Standards and Ethical Frameworks: HGA also monitors other relevant frameworks like the EU High-Level Expert Group’s Ethics Guidelines for Trustworthy AI (2019), the Universal Guidelines for AI (2018) by civil society groups, and ISO/IEC guidance on AI risk management. These reinforce similar themes – human agency, technical robustness, accountability – and HGA’s Policy is designed to be consistent with these broad consensus standards.

By grounding our Policy in these respected sources[28][10][29], HGA ensures that we are not acting in isolation but as part of a wider movement towards responsible AI. We will continue to update our practices as these frameworks evolve (for instance, adapting to new recommendations from UNESCO’s ongoing work or OECD’s updates in 2024 and beyond). Our goal is to exemplify how a mid-sized consulting-focused enterprise can implement global AI ethics principles in a practical, actionable manner – setting a positive example for our peers and maintaining the trust of those we serve.

Approval and Governance: This AI Ethics and Responsible AI Use Policy is approved by the CEO of Humanics Global Advisors as of the effective date noted. It will be reviewed on the schedule described herein, or more frequently as needed, and any material changes will be communicated to all stakeholders. All questions regarding this Policy should be directed to the HGA System Manager or the Compliance Officer at compliance@humanicsgroup.org. By following this Policy, we collectively ensure that the HGA Digital Platform remains a trusted, fair, and innovative environment where technology is used responsibly for the benefit of all participants.

[1] Recommendation on the Ethics of Artificial Intelligence | UNESCO

https://www.unesco.org/en/articles/recommendation-ethics-artificial-intelligence

[2] [7] [10] [12] [13] [14] [15] [18] [19] [20] AI principles | OECD

https://www.oecd.org/en/topics/sub-issues/ai-principles.html

[3] [16] [22] [24] [25] [27] HGA_Consultant_Contract_Template.docx

file://file-GA7v2hdnXhXEYmWj3q3gXG

[4] [11] [17] [21] [23] [26] [29] Automated Decision Making: Overview of GDPR Article 22 – GDPR Local

https://gdprlocal.com/automated-decision-making-gdpr/

[5] [6] [9] [28] The UNESCO Recommendation on the Ethics of Artificial Intelligence | Soroptimist International

https://www.soroptimistinternational.org/2024/07/18/the-unesco-recommendation-on-the-ethics-of-artificial-intelligence/

[8] thedocs.worldbank.org

https://thedocs.worldbank.org/en/doc/178331533065871195-0290022020/original/ProcurementRegulations.pdf

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Transparency and Explainability

Human Oversight and Accountability

Privacy and Data Protection in AI Systems

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User Rights: Contestability and Appeal

Compliance with Laws and Best Practices

Roles and Responsibilities

Implementation Timeline and Review

Reporting and Documentation

Breach Management and Corrective Actions

Enforcement and Compliance

References and Framework Alignment (Informative)

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