Project Report

University of Benin Draft Artificial Intelligence Policy

Submitted by

Falodun Abiodun, University of Benin, Edo State, Nigeria.

Abstract

The University of Benin acknowledges the potential significance of Artificial Intelligence (AI) in transforming the academic ecosystem, and the need to adopt AI in the activities of the institution. The use of AI in teaching, research is critical for the advancement of the university system. To enshrine AI in our university system, the university must develop an AI policy to address the use and challenges of AI. Therefore, the aim of this exercise is to develop a draft AI policy for the university of Benin. The UNIBEN AI policy drafted takes into consideration some parameters such as sensitization seminars and workshops, faculty members engage in discourse, acquainting themselves with AI's nuances and ethical considerations. Subsequently, the Senate convenes a diverse committee, comprising representatives from all faculties, non-teaching staff, and external experts from the private sector proficient in AI.

The AI Policy Drafting Committee meticulously collates and synthesizes these inputs, crafting a zero draft that encapsulates the university's values and commitments. Iterative feedback loops ensue as the zero draft undergoes scrutiny by faculty boards, refining the policy's contours to align with disciplinary nuances and practical exigencies. Upon culmination, the draft is submitted to the Senate for rigorous review and eventual approval, culminating in formal ratification by the Governing Council of the University of Benin.

The substantive policy framework delineates parameters for AI use across teaching, research, and community engagement endeavors, alongside robust mechanisms for oversight and accountability. Key provisions encompass procurement strategies, legal compliance, roles and responsibilities, responsible data stewardship, privacy safeguards, and capacity-building initiatives.

In conclusion, the University of Benin AI policy will help to fast-track the deployment of AI technology for research, teaching and community service for excellence, scholarship and effective service delivery.

Introduction

The University of Benin is one of the several institutions of higher learning in Nigeria. Over the years, it has played a very significant role in Nigeria’s march towards development in all sectors of the economy. Prof L.I. Salami is the 10th substantive Vice Chancellor. It was founded on 23rd November 1970. The vision of the university is to be a model institution of higher learning which ranks among the best in the world and is responsive to the creative and innovative abilities of the Nigerian people.

The Mission is to develop the human mind to be creative, innovative, research oriented, competent in areas of specialization, knowledgeable in entrepreneurship and dedicated to service. The university of Benin has 15 faculties, with over 80 academic programmes, and a student population of over 60,000. The programmes in the university are ICT driven and compliance with the CCMAS. Research and teaching are  central to the vision and mission of the University of Benin to offer solutions to society’s big problems and be a leading, global educational institution. The University of Benin (UNIBEN) is one of the top universities in Nigeria. UNIBEN is also a comprehensive university that is regarded as the most sought-after university in Nigeria. UNIBEN boasts of a dynamic leadership that is focused on improving the quality of education delivery at all levels in Nigeria.Therefore, the need to introduce artificial intelligence to enhance the mandate of the university cannot be overemphaise.

The objectives of the project: the objectives of this project include the following:

Promoting AI Research and Innovation: Foster a conducive environment for research and innovation in artificial intelligence within the university community, aiming for advancements in AI technologies and applications.

Ethical and Responsible AI Use: Establish guidelines and principles for the ethical and responsible development, deployment, and use of AI technologies, ensuring alignment with societal values and norms.

Integration of AI into Education: Incorporate AI education and training into the university of Benin curriculum across various disciplines to equip students with the necessary skills and knowledge for the AI-driven future workforce.

Collaboration and Partnerships: Facilitate collaboration and partnerships with industry, government, and other institutions to leverage resources, expertise, and opportunities for AI-related initiatives and projects.

Supporting AI Infrastructure and Resources: Provide the necessary infrastructure, resources, and support for AI research and development activities, including access to computing resources, datasets, and specialized equipment.

Promoting Diversity and Inclusion: Ensure diversity and inclusion in AI research and development efforts, aiming for equitable representation and participation across gender, race, ethnicity, and other demographics.

Community Engagement: use the knowledge of AI to strengthen community engagement and services rendered by the University of Benin.

Artificial Intelligence-Definition, History and Current Development

Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing speech, making decisions, and identifying patterns. AI is an umbrella term that encompasses a wide variety of technologies, including machine learning, deep learning, and natural language processing (NLP). Although the term is commonly used to describe a range of different technologies in use today, many disagree on whether these actually constitute artificial intelligence. Instead, some argue that much of the technology used in the real world today actually constitutes highly advanced machine learning that is simply a first step towards true artificial intelligence, or “general artificial intelligence” (GAI).

The history of artificial intelligence (AI) stretches back to ancient times, but its modern development began in the mid-20th century. Here's a concise overview:

1. Origins (Antiquity - 20th Century):

The concept of artificial beings and intelligent machines dates back to ancient civilizations like Greece, China, and Egypt.

In the 20th century, the development of electronic computers provided a foundation for AI research.

2. Birth of AI (1950s - 1960s):The term "artificial intelligence" was coined by John McCarthy in 1956, marking the official birth of the field.

Early AI research focused on symbolic reasoning and problem-solving, exemplified by programs like the Logic Theorist and General Problem Solver.

3. AI Winter and Expert Systems (1970s - 1980s):Despite initial optimism, progress in AI faced significant challenges, leading to a period known as the "AI winter," marked by funding cuts and skepticism.Expert systems, which used rule-based systems to mimic human expertise in specific domains, gained prominence during this time.

4. Neural Networks and Renewed Interest (Late 1980s - Early 2000s):Neural networks, inspired by the structure of the human brain, saw renewed interest, leading to advances in pattern recognition and machine learning. Applications like handwriting recognition and early speech recognition systems emerged.

5. Big Data and Deep Learning (2000s - Present):The proliferation of digital data and computational power paved the way for breakthroughs in machine learning, particularly deep learning. Deep learning, a subset of neural networks, achieved remarkable success in tasks like image recognition, natural language processing, and game playing.

AI in Africa. Universities in Nigeria are making efforts in embracing AI. The Management of VICBHE in collaboration with the National Open University of Nigeria led by the distinguished Prof Emeritus Peter Okebukola is championing this course through capacity-building of academic staff of universities, Polytechnics and colleges of Education. University of Benin is one of the first generation is making serious efforts and commitments for the deployment of AI technology in the institution for effective service delivery. The Module 8 participants have been trained in the ABC of artificial intelligence for delivery in higher education, and module 8 UNIBEN participants are well-equipped and future-ready to make UNIBEN first in AI in all ramifications.

SWOT Analysis:

Strengths:

1. Academic Excellence: The University of Benin (UNIBEN) is known for its academic excellence, which provides a fertile ground for implementing AI in various disciplines.

2. Infrastructure: UNIBEN has a solid infrastructure including laboratories, computing facilities, and internet connectivity, which are essential for AI implementation.

3. Research Culture: The university has a strong research culture, with faculty and students engaged in various research projects, providing opportunities for AI applications and innovations.

4. Skilled Workforce: UNIBEN has a pool of skilled faculty and researchers who can contribute to the development and implementation of AI technologies.

Weaknesses:

1. Resource Constraints: Limited financial resources and funding may hinder the implementation of AI projects and infrastructure development.

2. Infrastructure Limitations: Inadequate infrastructure such as outdated computers, software, and internet connectivity may pose challenges to effective AI implementation.

Opportunities:

1. Research Collaboration: Collaborating with industry partners, government agencies, and other academic institutions can provide opportunities for joint research projects and funding for AI initiatives.

2. Curriculum Enhancement: Integrating AI-related courses and modules into the curriculum can better prepare students for the future job market and foster interdisciplinary learning.

3. Industry Partnerships: Partnering with industry players can facilitate technology transfer, internship opportunities, and sponsored research projects in AI.

4. Community Engagement: Engaging with the local community and industry

5. Global Recognition: Establishing UNIBEN as a hub for AI research and innovation can attract international recognition, funding, and collaborations.

Threats:

2. Ethical Considerations: Ethical concerns surrounding AI, such as bias in algorithms, job displacement, and AI-driven decision-making, may spark controversies and public backlash.

Methodlogy for the development of the AI Policy for the University of Benin

The Strategies for the deployment of UNIBEN AI Policy will involve two approaches, namely the process and the contents of the AI policy.

The process for the deployment will include the following steps:

1. Conduct of sensitisation seminars and workshops on AI for members of staff.

2. Setting up of a Committee by Senate to draft the AI policy with members drawn from all Faculties; to also include non-teaching staff and some external members such as private sector professionals with expertise in AI.

3. Request by the AI Policy Drafting Committee to stakeholders to submit inputs.

4. The AI Policy Drafting Committee collates and synthesises all inputs.

5. Sharing of the zero draft to Deans for Faculty Board input.

6. Revision based on the inputs from the Faculty Boards

7. Submission of draft to Senate by the AI Policy Drafting Committee.

8. Review and approval by the Senate of the University of Benin.

9. Ratification by the University of Benin Governing Council.

The contents of the draft policy will include the following:

1. Acceptable level of AI use for teaching, research, community service and other activities of staff and students including academic papers and students’ project reports and theses.

2. Sanctions for transgression of acceptable levels of AI use.

3. Procurement plan for AI infrastructure and software.

4. Legal implications

5. Roles and responsibilities

6. Responsible data use

7. Capacity building

8. Full disclosure policy

9. Privacy and ethical considerations

10. Policy advocacy

11. Interdisciplinary collaboration

12. Diversity and inclusion

13. Monitoring and evaluation 

Proposed Contents of the Draft AI Policy

Introduction:The University of Benin (UNIBEN) acknowledges the transformative potential of Artificial Intelligence (AI) in various aspects of academia. These draft policies outline the ethical guidelines governing the use of AI in teaching, research, community service, and quality assurance at UNIBEN. The university is committed to ensuring that AI technologies are employed in a manner

This policy outlines the guidelines and principles governing the integration of Artificial Intelligence (AI) technologies in teaching at the University of Benin (UNIBEN).

2. Purpose:The purpose of this policy is to harness the potential of AI technologies to enhance teaching effectiveness, improve learning outcomes, and foster innovation in pedagogy while ensuring ethical and responsible use.

3. Ethical Considerations:All AI applications in teaching must adhere to ethical principles such as fairness, transparency, accountability, and privacy.

Educators should ensure that AI tools and algorithms used in teaching activities do not reinforce biases or discrimination and promote diversity and inclusion.

Students' rights to privacy and data protection must be respected, and informed consent should be obtained for the collection and use of any personal data.

4. Integration of AI in Curriculum:Faculty members are encouraged to explore the integration of AI technologies into course curricula to enhance teaching effectiveness and student engagement.

5. Training and Professional Development:UNIBEN shall provide faculty members with training and professional development opportunities to build their proficiency in using AI technologies for teaching.

6. Accessibility and Inclusivity:AI-based teaching tools and materials shall be designed with accessibility features to accommodate diverse learning needs, including those of students with disabilities.Educators shall be mindful of potential biases in AI algorithms and take proactive measures to ensure that teaching materials and assessments are inclusive and equitable.

7. Assessment and Evaluation:The effectiveness of AI applications in teaching shall be regularly assessed and evaluated based on predefined metrics, including learning outcomes, student engagement, and satisfaction.

Feedback from students and faculty members shall be solicited to identify strengths, weaknesses, and areas for improvement in AI-enabled teaching practices.

8. Intellectual Property Rights:Intellectual property rights associated with AI-based teaching materials, software, and innovations developed by faculty members shall be clearly defined and protected.Faculty members shall respect copyright laws and intellectual property policies when using third-party AI tools and resources in their teaching.

9. Continuous Improvement and Innovation:UNIBEN encourages faculty members to explore new AI technologies, pedagogical approaches, and teaching strategies to continuously improve the quality of education.Research and development initiatives focused on AI in education shall be supported to drive innovation and knowledge creation in the field.

10. Compliance and Oversight:UNIBEN shall establish mechanisms for monitoring and oversight to ensure compliance with this policy and relevant regulations governing the use of AI in teaching.A designated committee or office shall be responsible for reviewing proposed AI initiatives, conducting ethical assessments, and providing guidance on compliance matters.

11. Periodic Review and Updates:This policy shall be subject to periodic review and updates to reflect advancements in AI technology, changes in educational practices, and emerging ethical considerations.Feedback from faculty, students, and other stakeholders shall be solicited to inform revisions and improvements to the policy over time.

12. Implementation:This policy shall come into effect upon approval by the governing council of the University of Benin.Faculty members shall be notified of the policy and provided with resources and support for implementing AI technologies in their teaching practices.

13. Enforcement:Violations of this policy shall be subject to disciplinary action in accordance with UNIBEN's policies and procedures.

- Reports of non-compliance or ethical concerns regarding the use of AI in teaching shall be investigated promptly, and appropriate corrective actions shall be taken.

14. Communication: UNIBEN shall communicate this policy to all relevant stakeholders, including faculty members, students, staff, and administrators.Clear guidelines and procedures for implementing the policy shall be made available through official channels, such as the university's website and internal communications.

15. References: This policy shall be guided by relevant laws, regulations, and guidelines governing the use of AI in education, as well as best practices established by reputable organizations and institutions.

Research

1. Introduction:This policy outlines the guidelines and principles governing the integration of Artificial Intelligence (AI) technologies in research activities at the University of Benin (UNIBEN).

2. Purpose:The purpose of this policy is to facilitate the ethical and innovative use of AI in research activities to advance knowledge, address societal challenges, and promote academic excellence.

3. Ethical Considerations:All AI applications in research must adhere to ethical principles such as fairness, transparency, accountability, and privacy.

Researchers should ensure that AI tools and algorithms used in research activities do not perpetuate biases or discrimination and promote diversity and inclusion.

Participants' rights to privacy, informed consent, and data protection must be respected, and appropriate measures should be taken to safeguard sensitive information.

4. Integration of AI in Research:Researchers are encouraged to explore the integration of AI technologies into their research projects to enhance data analysis, modeling, and prediction capabilities.Researchers should ensure that the use of AI complements existing research methodologies and contributes to the advancement of knowledge in their respective fields.

5. Training and Capacity Building:UNIBEN shall provide researchers with training and capacity-building opportunities to enhance their proficiency in using AI technologies for research purposes.

6. Data Privacy and Security:Researchers must comply with data protection regulations and ethical guidelines when collecting, storing, and processing data for AI-driven research projects.Researchers should obtain appropriate approvals and permissions for accessing and using third-party datasets, ensuring compliance with legal and ethical standards.

7. Transparency and Reproducibility:Researchers using AI algorithms and models in their research should strive for transparency and reproducibility by documenting their methods, algorithms, and data sources.

8. Collaboration and Interdisciplinary Research:UNIBEN encourages collaboration and interdisciplinary research initiatives involving AI technologies to address complex challenges and promote innovation.Researchers from different disciplines are encouraged to collaborate on AI-driven projects.

9. Intellectual Property Rights:Intellectual property rights associated with AI-based research outcomes, software, and innovations developed by UNIBEN researchers shall be clearly defined and protected.

10. Compliance and Oversight:UNIBEN shall establish mechanisms for monitoring and oversight to ensure compliance with this policy and relevant regulations governing the use of AI in research.A designated committee or office shall be responsible for reviewing proposed AI-driven research projects, conducting ethical assessments, and providing guidance on compliance matters.

11. Periodic Review and Updates:This policy shall be subject to periodic review and updates to reflect advancements in AI technology, changes in research practices, and emerging ethical considerations.

12. Implementation:This policy shall come into effect upon approval by the appropriate governing body of the University of Benin.Researchers shall be notified of the policy and provided with resources and support for implementing AI technologies in their research endeavors.

13. Enforcement:Violations of this policy shall be subject to disciplinary action in accordance with UNIBEN's policies and procedures.Reports of non-compliance or ethical concerns regarding the use of AI in research shall be investigated promptly, and appropriate corrective actions shall be taken.

14. Communication:UNIBEN shall communicate this policy to all relevant stakeholders, including researchers, research administrators, ethics committees, and funding agencies.

Clear guidelines and procedures for implementing the policy shall be made available through official channels, such as the university's website and internal communications.

15. References:This policy shall be guided by relevant laws, regulations, and guidelines governing the use of AI in research, as well as global best practices.

Community Service

1. Ethical Principles

Transparency: All AI systems used in community service initiatives must be transparent in their operations and decision-making processes. Users should understand how AI algorithms function and the factors influencing their outcomes.

Fairness: AI applications should be designed and implemented to promote fairness and equity, avoiding biases based on factors such as race, gender, ethnicity, or socioeconomic status.

Accountability: Clear lines of accountability must be established for the development, deployment, and maintenance of AI systems

Privacy and Data Security: Protecting the privacy and security of individuals' data is paramount.

Beneficence: AI technologies should be deployed to maximize benefits and minimize harm to the community.

Guidelines for AI Use in Community Service

Needs Assessment: Before implementing AI technologies in community service projects, conduct a thorough needs assessment to identify areas where AI can effectively contribute to addressing societal challenges.

Stakeholder Engagement: Involve community members and relevant stakeholders in the design, development, and implementation of AI-driven initiatives to ensure their needs and concerns are adequately addressed.

Algorithmic Transparency: Ensure that AI algorithms used in community service are explainable and interpretable.

5. Compliance and Enforcement

Establish mechanisms for monitoring compliance with AI ethical policies and guidelines.

Quality Assurance: AI will be useful in the following QA tasks: Predictive Analytics, Personalized learning,automated assessment and virtual assistants, quality monitoring and fraud detection, enrollment management, adaptive learning platforms, resource allocation.

By integrating AI into quality assurance processes at the University of Benin, the institution can enhance efficiency, accuracy, and fairness while maintaining the highest standards of academic excellence and integrity.

1. Ethical Principles

Transparency: All AI-driven quality assurance processes must be transparent, with clear explanations of how AI algorithms operate and the criteria used to make decisions.

Guidelines for AI Use in Quality Assurance: Selection and Training of AI Models: Choose AI models and algorithms for quality assurance purposes based on their suitability, accuracy, and alignment with the university's objectives.

2. Validation and Testing: Thoroughly validate and test AI systems before deployment to ensure their accuracy, reliability, and fairness. Regularly assess and monitor the performance of AI models to maintain quality standards.

3. Data Quality and Integrity: Ensure that data used to train AI algorithms for quality assurance purposes are accurate, relevant, and representative of the population being assessed.

Interpretability and Explainability: AI systems used in quality assurance should be designed to provide interpretable and explainable results.

4. Bias Mitigation: Employ techniques to detect and mitigate biases in AI systems, such as algorithmic audits, fairness-aware algorithms, and diverse training data sets.

5. Continuous Improvement: Foster a culture of continuous improvement in AI-driven quality assurance processes. Solicit feedback from stakeholders and adapt AI systems accordingly to address emerging challenges or opportunities for enhancement.

6. Compliance with Regulations: Ensure that AI-driven quality assurance activities comply with relevant laws, the National Universities Commission, and ethical guidelines governing data privacy, academic integrity, and other pertinent areas.

7. Compliance and Enforcement: Establish mechanisms for monitoring compliance with AI ethics policies and guidelines in quality assurance activities.Designate a committee tasked with overseeing AI initiatives in quality assurance and ensuring adherence to ethical standards.

8. Review and Revision

Regularly review and revise AI ethics policies and guidelines for quality assurance in response to technological advancements, regulatory changes, and feedback from stakeholders.

Ethical Consideration

Ethical considerations in integrating AI in higher education refer to the careful examination and adherence to moral principles and values when implementing artificial intelligence technologies in educational settings. This involves addressing various ethical issues such as Bias, Equity, Privacy, Fairness,Transparency, Accountability.

Principles of Ethical AI. The following principles shall guide the development, deployment, and use of AI systems within the University of Benin:

a. Transparency: AI systems used within the university must be transparent, with clear explanations of their functions, decision-making processes, and limitations provided to stakeholders.

b. Accountability: Responsibility for the development, deployment, and outcomes of AI systems rests with the university administration, faculty, and staff involved in their implementation.

c. Fairness: AI systems must be designed and implemented in a manner that promotes fairness, equity, and inclusion, while mitigating biases and discrimination.

d. Privacy and Data Protection: The university shall uphold the privacy rights of individuals and ensure compliance with relevant data protection laws and regulations in the collection, storage, and processing of data used by AI systems.

e. Safety and Security: AI systems must be designed and maintained to prioritize the safety and security of users, data, and the university’s infrastructure against potential risks and threats.

f. Human Oversight: While AI systems may automate certain tasks, they should always be subject to human oversight and intervention to ensure ethical decision-making and accountability.

Use Cases and Applications

The University of Benin shall utilize AI technologies in various domains, including but not limited to:

a. Academic Support: AI-powered tools may be employed to support teaching, learning, and academic research, such as intelligent tutoring systems, plagiarism detection software, and research analytics platforms.

b. Administrative Efficiency: AI systems may be deployed to streamline administrative processes, optimize resource allocation, and enhance operational efficiency across different departments and administrative units.

c. Student Services: AI-driven chatbots and virtual assistants may be implemented to provide personalized support and guidance to students, including academic advising, course selection, and career counseling.

Ethical Review and Oversight

All AI projects and initiatives undertaken by the University of Benin shall undergo ethical review and oversight to ensure compliance with the principles outlined in this policy. The university shall establish an Ethics Committee comprised of multidisciplinary experts to evaluate the ethical implications of proposed AI initiatives, monitor their implementation, and address any ethical concerns that may arise during their deployment.

Education and Training

The university shall provide education and training on the ethical use of AI to faculty, staff, and students involved in the development, deployment, and use of AI technologies. Training programmes shall include modules on AI ethics, bias mitigation, data privacy, and responsible AI practices to promote awareness and understanding of ethical considerations among stakeholders.

Transparency and Accountability

The University of Benin shall maintain transparency and accountability in its use of AI technologies by providing clear documentation of AI systems and algorithms used within the university, and establishing mechanisms for stakeholders to raise concerns or report ethical issues related to AI use, and to regularly perform audits and assessments of AI systems to evaluate their compliance with ethical standards and identify areas for improvement.

Compliance and Review: This policy shall be reviewed periodically to ensure its alignment with evolving ethical standards, technological advancements, and regulatory requirements governing AI use. Non-compliance with this policy may result in disciplinary action, including but not limited to suspension or termination of AI projects and initiatives found to violate ethical principles.

Implementing the University of Benin draft AI Policy:

Implementing an AI policy at the University of Benin would require a multi-faceted approach involving the folowing important factors:

Computational Resources: Investing in high-performance computing (HPC) infrastructure to support AI research and applications.

Data Infrastructure: Establishing data storage and management systems to securely handle large volumes of data required for AI projects.

Networking Infrastructure: Ensuring robust network connectivity to facilitate data transfer and collaboration among researchers and stakeholders.

Hardware and Software: Procuring AI-specific hardware (GPUs, TPUs) and software tools (frameworks, libraries) necessary for development and deployment of AI solutions.

Capacity building: Developing training programs and workshops to upskill faculty, researchers, and students in AI theory, methodologies, and applications.

Collaboration Initiatives: Facilitating partnerships with industry experts, research institutions, and AI communities to foster knowledge exchange and collaboration.

Internship and Research Opportunities: Creating opportunities for students to engage in AI research projects, internships, and hands-on experiences.

Faculty Development: Supporting faculty members in advancing their expertise in AI through research grants, sabbaticals, and professional development activities.

Institutional Frameworks:

Governance Structures: Establishing clear governance structures and committees responsible for overseeing AI research, development, and ethical considerations.

Ethical Guidelines: Formulating ethical guidelines and protocols for AI research and applications to ensure responsible and transparent use of AI technologies.

Compliance and Regulation: Adhering to national and international regulations governing AI, data privacy, and intellectual property rights.

Monitoring and Evaluation: Implementing mechanisms to monitor the progress and impact of AI initiatives and policies, with regular evaluations and feedback loops for continuous improvement.

Support Services:

Technical Support: Providing technical support services for researchers and students to troubleshoot issues related to AI tools, software, and infrastructure.

Consultation Services:Offering consultation services for project design, implementation, and optimization of AI solutions across various domains.

Resource Allocation: Allocating funding and resources to support AI-related projects, including grants, scholarships, and research facilities.

Monitoring and Evaluation

Monitoring and evaluation (M&E) of AI systems is important for the effective and efficient delivery of AI in the University of Benin. The various steps involved in the M and E are as follows:

Performance Metrics: UNIBEN should establish a reliable and efficient performance metrics. The parameters involved include accuracy, precision and reliability depending on the AI tool deployed.

Bias and Fairness: There is need to reduce or to the barest minimum the biases associated with the use of AI. Conscious efforts should be made to monitor the use of AI to ensure fairness different demographic groups.

Ethical Compliance: It is very critical to ensure full compliance to ethical guidelines in the use of AI for teaching, research, and community service.  This includes assessing whether the AI system respects user privacy, is transparent in its decision-making process, and adheres to legal and regulatory requirements.

Safety and Robustness: UNIBEN AI Policy should be evaluated for safety. This involves  testing the system against adversarial attacks, ensuring that it behaves reliably in different environments, and identifying potential failure modes.

User Feedback: The UNIBEN AI policy should Incorporate feedback from users inorder to assess the impact.

Interpretability and Explainability: Deliberate efforts should be made to ensure that AI systems should be evaluated for their interpretability and explainability. This involves evaluating how well the system can explain its decisions and whether these explanations are understandable and trustworthy to staff, students and the university community.

Human-AI Interaction: AI systems should be evaluated regularly for usability and end user experience between the humans and the the Ai systems. To achieve this, factors such as responsiveness, natural language understanding, and the ability to effectively collaborate with human users.

Effective Documentation and Reporting: Finally, it is  important to document the M&E process and report findings transparently to stakeholders. This includes detailing the evaluation methodologies, results, and any actions taken to address identified issues.

The deployment of these tools and metrics into the monitoring and evaluation process, UNIBEN will ensure that AI systems are developed, deployed, and maintained responsibly, ultimately maximizing their benefits while minimizing risks and potential harm.

Funding model: The deployment of AI in the University of Benin will involve huge capital because of the software, human capacity building, the hardware, and the implementation. Hence, the successful implementation of the policy will depend largely on the funds availability. Though it is capital intensive, but it is achievable.  The funding of AI implementation in the University of Benin can be derived from two major sources namely internal and external sources.

The internal sources will involve the budgetary provision by the university management and ratified by the Governing Council for 5% of the university budget to be used to fund AI.

The external funding will involve grants from unilateral, bilateral, and multilateral funding agencies. International agencies will gladly support the implementation of Ai in the University of Benin. Another strategic approach is the quadrupole helix model that will involve the academia, the industry, the private sector and the government. As a matter of fact, an endowment can be established to have a Centre of Excellence in AI for teaching, research, and community service. The proposed Centre will be funded by captains of industries, alumni, and industry partners.

The sustainability of the AI in UNIBEN will be achieved if the Centre of Excellence in Artificial Intelligence is well funded. The Centre will also have the mandate to train and organize capacity building for corporate organizations, other universities, polytechnics, and colleges of Education.

Short certificate courses in the ABC of artificial intelligence organize by the Centre of AI in UNIBEN will also sustain the Centre.

Conclusion:The robust ICT infrastructure of the University of Benin certainly will be harnessed to deploy AI technology to the institution. By adopting a holistic and inclusive approach to AI policy, UNIBEN can harness the transformative potential of AI while safeguarding against its risks and ensuring that it serves the common good. Writing and developing a robust AI policy document for the University of Benin will enhance the quick deployment of AI technology for effective service delivery, scholarship, innovation and excellence. It will make UNIBEN to be future ready leading to the production of market-ready graduates. 

References

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2. European Union Agency for Fundamental Rights. (2018). Artificial intelligence: The implications of AI-powered decision-making for fundamental rights. Retrieved from https://fra.europa.eu/en/publication/2018/artificial-intelligence-implications-ai-powered-decision-making-fundamental-rights

3. Zwitter, A., & Marusic, B. (2019). Artificial Intelligence in Europe: Ethics, Rights, and Policy Challenges. Routledge.