Project Report

University of Lagos Draft Artificial Intelligence (AI) Policy

'Tunde Ope-Davies

University of Lagos

Abstract

 Artificial Intelligence (AI) is rapidly transforming various aspects of society, spanning from health, commerce, politics, agriculture and other areas. It has therefore become imperative for higher education institutions in Nigeria to harness the benefits of this amazing technology. As AI technologies become increasingly pervasive in academia, it is imperative for our own university here  to establish clear guidelines and frameworks to govern the ethical, legal, and practical aspects of AI usage within its academic and administrative functions. This proposal outlines the development of an Artificial Intelligence (AI) Policy for the University of Lagos. The policy aims to explain and describe how our institution can leverage AI technology to enhance various aspects of its operations, in various academic and administrative domains including data management, decision-making, teaching, research, and services. It offers a comprehensive plan that encompasses how AI can revolutionize academic and demonstrative sectors at the University of Lagos. The additional objective of this policy is to show how by harnessing the potential of AI, we can galvanize academic excellence, research, and innovation, while addressing ethical and societal implications. The framework includes a conceptual model, methods, SWOT analysis, monitoring and evaluation, and funding strategies to ensure successful implementation. It highlights the importance of implementing AI policy by this university and how this implementation will enhance efficiency, innovation, and overall academic quality.  The proposal concludes by emphasizing the significance of AI in higher education and the need for a comprehensive policy to guide its integration here in our institution.

Introduction

Artificial Intelligence (AI) has become a transformative technology with the potential to revolutionize various sectors, including education. Recognizing the importance of AI in enhancing university processes is a reflection of the pervading and evolving influence of AI in every aspect of our society. The world is witnessing an exponential rise in Artificial Intelligence (AI) applications across diverse sectors. From healthcare and education to finance and transportation, AI is revolutionizing how we live and work. As a leading academic institution in Africa, the University of Lagos (UNILAG) needs to be proactive in embracing AI and its potential benefits. This necessitates the development of a robust AI policy that guides research, development, and responsible use of AI technologies within the university.  In the educational setting for instance, AI offers opportunities for enhancing data management, decision-making, research services, and student assessment. Several studies highlight the positive impact of AI on higher education. For instance, research by Zhang (2021) emphasizes the opportunities AI brings for improving data management, decision-making, and educational services. Additionally, Zawacki-Richter et al. Zawacki‐Richter et al. (2019) discuss the establishment of AI research institutes in universities, showcasing the growing importance of AI in academia.   Despite the potential benefits of AI in higher education, there is a lack of structured policies guiding its implementation in many universities. This gap hinders the effective utilization of AI technologies to enhance teaching, research, and overall academic excellence. Therefore, there is a need for a comprehensive AI Policy tailored to the specific needs and context of the University of Lagos. Without clear guidelines and protocols, there is a risk of underutilizing AI resources, compromising data security, and failing to maximize the technology's potential for academic and administrative purposes.

While AI offers numerous benefits to universities like UNILAG, its adoption also presents challenges. These challenges include may include (i) ethical considerations surrounding AI bias, privacy infringement, and algorithmic accountability. (ii)  Legal issues related to intellectual property rights, data protection, and liability. (iii) Socio-economic implications such as job displacement, inequality, and digital divide. (iv) Technical challenges concerning data quality, algorithm transparency, and system robustness.

The necessity of drafting this policy framework therefore is predicated to  address these challenges so that our university will avoid encountering ethical dilemmas, legal disputes, socio-economic backlash, and technical failures in its AI initiatives.

Artificial Intelligence- Definitions, Short History and Current Development

AI refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning, reasoning, problem-solving, perception, and language understanding.  Artificial intelligence is a broad field of computer science focused on creating intelligent machines that can mimic human cognitive functions such as learning, problem-solving, and decision-making. AI encompasses various techniques, including machine learning, robotics, deep learning, natural language processing, and computer vision. AI encompasses a wide range of techniques and applications, including machine learning, natural language processing, computer vision, robotics, and expert systems. AI has also been described as  the quest to create machines that can exhibit intelligence similar to or surpassing that of humans. This involves not only replicating specific cognitive abilities but also understanding the nature of intelligence itself and the ethical implications of creating intelligent machines.

The history of AI dates back to the mid-20th century when pioneers like Alan Turing and John McCarthy laid the theoretical foundations. Significant advancements have occurred in recent decades, driven by improvements in computational power, data availability, and algorithmic innovation. Today, AI technologies are ubiquitous, powering virtual assistants, recommendation systems, autonomous vehicles, medical diagnosis tools, and more.  Current developments in AI encompass a wide range of applications, from face recognition systems to intelligent finance and educational tools. 

A more specific historical trajectory highlights the following timeline:

The history of AI is a fascinating journey that spans over several decades. Here's a brief overview:

1950s - Birth of AI:** The term "artificial intelligence" was coined in 1956 at the Dartmouth Conference. Early pioneers like Alan Turing and John McCarthy laid the groundwork for AI as a field of study.

1960s - Symbolic AI:  Research focused on symbolic or rule-based AI, which used formal symbols to represent knowledge and logic to manipulate those symbols.

1970s-1980s - Expert Systems and Knowledge-Based Systems:** AI researchers developed expert systems capable of mimicking the decision-making abilities of human experts in narrow domains. This era saw the rise of symbolic AI techniques like rule-based systems and knowledge representation.

1990s - Neural Networks Resurgence:** Neural networks, inspired by the human brain, regained popularity with the development of backpropagation algorithm. This led to advancements in machine learning and pattern recognition.

2000s - Big Data and Deep Learning:** The availability of massive datasets and increased computational power fueled the rise of deep learning, a subfield of machine learning focused on neural networks with many layers. Deep learning achieved remarkable results in image and speech recognition, natural language processing, and other domains.

010s - AI Boom and Ethical Concerns:** The 2010s witnessed an explosion of AI applications across industries, from virtual assistants like Siri and Alexa to autonomous vehicles and advanced robotics. However, concerns about AI ethics, including bias in algorithms, privacy issues, and job displacement, gained prominence.

2020s - Continued Advancements and Ethical Frameworks:** AI continued to advance rapidly, with breakthroughs in reinforcement learning, generative models, and AI ethics. Efforts to develop ethical frameworks and guidelines for responsible AI deployment gained momentum, aiming to address societal challenges and ensure AI benefits humanity.

Current developments in AI include the following key elements:

Continued Advancements in Deep Learning:** Researchers are exploring techniques to improve the performance, efficiency, and interpretability of deep learning models.

AI in Healthcare AI is transforming healthcare through applications like medical image analysis, drug discovery, personalized medicine, and predictive analytics for patient care.

Autonomous Systems: Progress in AI is driving the development of autonomous systems, including self-driving cars, drones, and robotic assistants.

Natural Language Processing (NLP): NLP techniques are advancing rapidly, enabling machines to understand and generate human language more accurately, leading to applications like language translation, sentiment analysis, and chatbots.

Ethical AI: There's a growing emphasis on ethical AI development, including transparency, fairness, accountability, and inclusivity in AI systems to mitigate potential harms and ensure equitable outcomes.

AI and Climate Change AI is being leveraged to address climate change challenges, including climate modeling, renewable energy optimization, and environmental monitoring.

AI Regulation and Governance: Governments and international organizations are increasingly focusing on AI regulation and governance to manage risks, protect privacy, and promote responsible AI deployment.

These developments reflect the ongoing evolution of AI, with both promising opportunities and important challenges to address.

While AI research and development (R&D) are rapidly growing globally, Africa remains a nascent player. Apart from Mauritius that has made some quantum leap in the use of AI, other countries in Africa are just waking up to realize the immense potential in using AI in all sectors of their national life. Nevertheless, one can argue that there’s a growing awareness of AI's potential to address challenges in agriculture, healthcare, education, and governance. Africa is thus rapidly embracing AI, with countries like South Africa, Egypt, and Nigeria investing in AI research and development. However, the continent faces challenges like inadequate infrastructure, limited access to data, and ethical concerns.

SWOT Analysis

In developing this policy document, it is important to keep in focus the SWOT analysis presented in the document.

Strengths:

- Strong academic expertise in relevant disciplines.

- Established research infrastructure and data resources.

- Commitment to innovation and excellence.

- Supportive leadership and governance structure.

Weaknesses:

- Limited awareness and understanding of AI among stakeholders.

- Lack of dedicated funding for AI initiatives.

- Potential resistance to change from traditional academic practices.

- Dependence on external partners for technical expertise.

Opportunities

- Collaboration with industry partners for research and development.

- Integration of AI into curriculum and pedagogy.

- Enhancement of administrative efficiency and student services.

- Contribution to national and global AI initiatives.

Threats

- Ethical and legal risks associated with AI misuse.

- Competition for talent and resources in the AI ecosystem.

- Rapid technological obsolescence and evolving regulatory landscape.

- Potential negative impacts on employment and societal equity.

Methodology for the Development of the AI Policy

The proposed AI Policy for the University of Lagos will include guidelines for integrating AI technologies in teaching, research, student services, and administrative processes. It will outline strategies for data management, curriculum development, faculty training, and infrastructure upgrades to support AI implementation.  *

The policy will include how  AI can improve teaching methods, personalize learning experiences, and streamline administrative processes; enhanced efficiency and innovation in various academic areas.

The AI policy for the University of Lagos should also include guidelines for data privacy, algorithm transparency, faculty training, student support services, and ethical considerations. It will present and demonstrate protocols for integrating AI tools in teaching, research, student assessment, and administrative functions while ensuring compliance with regulatory standards.

Developing an AI policy for UNILAG requires the following systematic approach:

(i). Research and Analysis: We will conduct a comprehensive review of existing AI policies in academia, government, and industry. We need to analyze relevant laws, regulations, ethical guidelines, and best practices.

  (ii)  Stakeholder Engagement: It is important to engage faculty, students, administrators, legal experts, ethicists, and industry partners in discussions and workshops to gather diverse perspectives and insights.

  (iii). Drafting and Review: As we set up the multidisciplinary task force to draft the AI policy document, we will incorporate inputs from these stakeholders to enrich the proposal. We will review the draft iteratively to ensure clarity, coherence, and feasibility.

  (iv). Approval and Implementation: We anticipate that after exhausting all the stages in developing the policy, we present the document to the Director of Academic Planning and the Academic Programmes Committee (APC) who will send  the draft  to the Senate of the  University of Lagos for approval. The document contains  an implementation plan with clear timelines, responsibilities, and monitoring mechanisms.

Proposed Contents of the Draft AI Policy

In this document we have the following key elements to guide its implementation:

(a) Scope: We provide some definitions of AI and the types of AI activities covered within the university.

(b) Research & Development. We propose guidelines that will guide the deployment of responsible AI in research, data governance, and collaboration.

(c) Education & Training: The use of AI for education and training. Here we suggest relevant tools and applications that may be used in this regard. We demonstrate how to integrate AI concepts and ethics into existing curricula and provide specialized training programs.

(d) Governance: Each unit and arms of the university involved in the implementation must be trained. The Academic Planning Office must ensure that it outlines the roles and responsibilities of various stakeholders in implementing the policy.

(e) Intellectual Property: In this document, we suggest how intellectual property concerns should be addressed. Office for research management must continue to play this important by strengthening set standards to guide ownership and use of intellectual property generated through AI research. International best practice must guide what we do here at the University of Lagos

(f) Ethical Considerations: This document shows how ethical considerations must be handled. It is important to implement principles like fairness, transparency, accountability, and human control in AI development and deployment. The following ethical considerations form part of the contents of this policy:

(i) Bias & Fairness: We must ensure that AI systems don't perpetuate societal biases based on race, gender, or other factors.  (ii) Transparency & Explainability: We must develop AI systems that are transparent in their decision-making processes.

(iii) Privacy & Security: The university must ensure that we protect personal data collected and utilized for AI development and operations.

(iv) Human Control: As part of the guidelines to be observed in implementing the policy, we must ensure that key and experienced ICT staff are able to maintain control over AI systems and be able to override decisions when necessary.

Some of the specific areas that AI can improve what we do include the following:

Implementing AI policy at our university will bring numerous benefits across various domains. This proposal therefore suggests the following  specific areas where AI can be deployed in our institution:

(a) Student Support and Engagement

We can develop AI-powered chatbots can provide instant support to students regarding course registration, scheduling, financial aid inquiries, and general information about the university.

   Additionally, personalized learning platforms can be integrated into students' learning styles and pace, providing tailored resources and recommendations.  AI can also be used to analyze student data to identify at-risk students who may need additional support or intervention.

(b) Teaching and Learning Enhancement:

   As our university faces the challenge of increased enrolment, AI-based tutoring systems can offer personalized feedback and guidance to students, supplementing traditional teaching methods. In the same vein, automated grading systems can speed up the grading process for assignments and exams, freeing up instructors' time for more meaningful interactions with students. By adopting Virtual reality (VR) and augmented reality (AR) technologies powered by AI, we can create immersive learning experiences, enhancing understanding and retention of complex concepts.

(c) Research and Development

   This proposal argues that AI has become the leading technology in accelerating front-end innovations in research and development. For instance  AI algorithms can be used to  analyze vast amounts of research data to discover patterns, trends, and insights that may not be immediately apparent to human researchers.

 Another key technologies in AI for research is  Natural language processing (NLP) which can  can assist in literature reviews, summarizing articles, and generating hypotheses. Likewise,  AI-driven simulations can model complex phenomena, allowing researchers to test hypotheses and conduct experiments in virtual environments.

(d)  Administrative Efficiency. As we strive to adopt AI in this university, it will be discovered that  AI can automate administrative tasks such as scheduling meetings, managing emails, and organizing documents, increasing efficiency and reducing administrative burden. AI can also provide predictive analytics which can optimize resource allocation, budgeting, and planning based on historical data and future projections.  Equally, AI-powered systems can enhance campus security through surveillance, facial recognition, and anomaly detection.

(e). Accessibility and Inclusivity

   We argue that AI technologies can improve accessibility for students with disabilities by providing alternative formats for learning materials, such as audio descriptions or text-to-speech conversion. Moreover, natural language processing can assist students with language barriers by offering translation services or simplifying complex language.

( f )  Student Recruitment and Admissions

   As mentioned earlier, AI  has become critically important in providing student services. AI-driven algorithms can analyze applicant data to identify promising candidates and predict their likelihood of success at the university. In a similar vein, chatbots and virtual assistants can provide instant support to prospective students, answering questions about admissions requirements, programs offered, and campus life.

(g) Alumni Relations and Fundraising

   Crowdfunding has become a new way of generating funds for AI can analyze alumni data to identify potential donors and personalize fundraising campaigns to maximize donations.

   - Chatbots can engage alumni through personalized communications, event invitations, and updates on university initiatives.

By strategically implementing AI policies in these areas, universities can enhance student experience, streamline operations, advance research, and foster innovation across the campus ecosystem. In more specific terms, implementing this policy in digital humanities have the capacity of achieving the following:

(i) Artificial intelligence accelerates the process of carrying out research and analyzing data in humanities by providing technologies and applications that transform traditional methods in humanities

This means that AI enables researchers in digital and traditional humanities to analyze large amounts of data and uncover patterns and insights at speeds previously unattainable, allowing for the creation of more dynamic ways to present historical and cultural content to potentially reach a broader audience.

(ii) The application of AI in Digital Humanities (DH)  enhances  algorithmic sensitivity to humanistic complexity

This implies that by applying AI to DH research and projects, scholars are able to advance algorithmic methodologies to more effectively interpret the dense, qualitative data prevalent in humanities research.

(iii)  AI can improve the prospect of synthesizing cross-disciplinary frameworks in Digital Humanities

This  means the scholars and researchers in digital humanities or traditional humanities can  seamlessly establish a transdisciplinary dialogue  with other areas of research and academic programmes which will help to  integrate the distinct lexicons and methodological constructs of AI and humanities researchers.  By crafting a shared semantic and operational framework, this approach can pave the way for seamless intellectual exchange and collaborative innovation between these divergent fields.

Implementing the Draft Policy

The Academy Planning Office in conjunction with Deans, Heads of Department, Directors of Research Centres and Heads of Units must be involved in the implementation of this AI policy. It will therefore involve collaboration between academic departments, administrative units, and IT services. Training programmes, workshops, and awareness campaigns will be conducted to familiarize stakeholders with AI tools and protocols. In order to ensure the success of this policy we must conduct regular assessments and feedback mechanisms so as to monitor the policy's effectiveness.

This policy should be a living document, reviewed and updated periodically to reflect evolving technological advancements and ethical considerations. By adopting a proactive and responsible approach to AI, UNILAG can solidify its position as a leader in innovation and pave the way for a future where AI benefits all.

Monitoring and Evaluation

This proposal suggests processes and guidelines for implementing this policy at our university. A special task force under the aegis of the Director of Academic Planning should be constituted to provide oversight function in monitoring and  evaluating the implementation of the policy. This continuous monitoring and evaluation of the AI policy will be essential to assess its impact on teaching outcomes, research productivity, operational efficiency, and student satisfaction. Key performance indicators will be identified to measure the policy's success and identify areas for improvement.

Funding

This document proposes a number of possible funding windows for the implementation of this policy. Such funding will be deployed to handle important components such as  AI infrastructure, training programmes and other associated expenses to ensure a successful implementation of the policy. The university may explore partnerships with industry stakeholders, research grants, and internal budget allocations to support the AI policy's sustainability. . Additionally, allocating a portion of the university budget to AI development will ensure sustained progress in this area. Government grants and research funding agencies.  Corporate partnerships and industry collaborations, Philanthropic donations from alumni and benefactors, internal reallocation of resources and budget prioritization.  We wish to also suggest that a dedicated budget allocation  should be made for AI research, infrastructure development, capacity building, and compliance monitoring is essential to ensure the sustainability and effectiveness of the policy.

Conclusion:

We argue that the implementation of an AI policy at our university  will have significant implications across various dimensions: (i) Academic Excellence: AI can enhance teaching, learning, and research outcomes, positioning UNILAG as a leader in innovation and knowledge creation. ( ii ) Ethical Leadership: By adopting responsible AI practices, UNILAG can uphold ethical principles, promote transparency, and foster public trust in its AI initiatives. (iv) Socio-Economic Impact: UNILAG's AI policy can contribute to economic development, job creation, and societal well-being by addressing societal challenges and fostering inclusive growth. (iv) Global Collaboration: Aligning with international standards and best practices will facilitate collaboration with global partners, enabling UNILAG to participate in cutting-edge research and innovation networks.

In conclusion, the development of an AI Policy for the University of Lagos presents an opportunity to harness the potential of AI technology for academic advancement. By strategically integrating AI into various university functions, the policy aims to enhance teaching quality, research outcomes, and overall operational efficiency.. By establishing clear guidelines, promoting awareness, and fostering a culture of innovation, the university can position itself as a leader in AI integration within the Nigerian higher education landscape. Through proactive implementation and continuous evaluation, the University of Lagos can position itself as a leader in AI-driven education. By adopting a systematic approach encompassing research, stakeholder engagement, drafting, and implementation, UNILAG can establish itself as a responsible steward of AI technology, driving innovation, excellence, and societal impact in Nigeria and beyond.

References

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Webography

Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig ([https://www.amazon.com/Artificial-Intelligence-A-Modern-Approach/dp/0134610997](https://www.amazon.com/Artificial-Intelligence-A-Modern-Approach/dp/0134610997))

The Algorithmic Justice League ([https://www.ajl.org/](https://www.ajl.org/))

African Institute for Mathematical Sciences (AIMS) ([https://nexteinstein.org/](https://nexteinstein.org/))

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation by the Future of Humanity Institute, University of Oxford ([https://arxiv.org/pdf/1802.07228](https://arxiv.org/pdf/1802.07228))