Authored By: Faith Malama
University of Zambia
The rapid growth of Artificial intelligence (AI) has outpaced the legal and ethical frameworks designed to govern it. Systems capable of analysing vast amounts of data and making complex predictions now influence access to services, opportunities and even liberty often with limited transparency. Against this backdrop, the regulation of AI becomes essential as without clear rules, safeguards, and accountability mechanisms these technologies risk entrenching bias, undermining privacy and eroding fundamental rights.
Artificial Intelligence refers to computer systems that are designed to perform tasks which normally require human intelligence such as recognizing patterns, making decisions, or understanding language.[1] AI has experienced rapid development in recent years and is now transforming many industries including healthcare, finance, and transportation thereby and reshaping society as we know it. The reason for such rapid development includes the fact that AI has the ability to process very large volumes of data at high speed, allowing it to generate decisions that are faster and in certain instances more precise than those made by humans.[2] Mr Joseph Chirwa during a seminar on Legal Writing in the Era of Artificial Intelligence hosted by the UNZALAW Legal Editorial Board also noted that with the development of AI, research has been made easier because AI enables individuals to have access to so much information as it compiles data from multiple sources that would have otherwise taken an ordinary human much longer to compile and as such these systems relieve human beings of workloads and makes tasks more manageable.[3]
AI offers substantial benefits that extend well beyond rapid data processing, improved efficiency, automation, and regulation of insights. It has the potential to transform healthcare by supporting the development of new treatments and cures, to stimulate economic growth, to contribute to efforts to address climate change, and to increase scientific innovation among other advantages.[4] Having explored the concept of AI and its advantages, it is equally important to examine its potential risks and why legal oversight is mandatory.
The Regulatory Gap: Risks and Legal Challenges of Unchecked AI
While Artificial Intelligence offers many benefits, it is equally important to examine its risks and the corresponding need for legal frameworks to govern its use as without this effective regulation AI can create serious dangers.
One of the most prominent concerns is the potential infringement of human rights, particularly the right to privacy which is a fundamental right provided for in Article 17 of the Constitution of Zambia.[5] Because AI systems depend on very large datasets to identify patterns, the information used for training often contains sensitive and personal data and some datasets can be re identified meaning that individuals’ supposedly anonymised information thought to be private and securely protected may be exposed.[6]
Additionally, AI also raises concerns beyond privacy particularly regarding whether it can respond appropriately to new or unusual situations that fall outside training data. These systems rely on input data that is collected from multiple sources the categorized and processed after which the AI detects and applies these patterns it has been programmed to learn.[7] This design becomes problematic when the system encounters circumstances that were not anticipated during development or when the underlying data has become outdated. In healthcare for example, AI struggles with continuous learning because medical knowledge and clinical processes evolve rapidly so tools built on static datasets risk becoming obsolete, leading to a decline in accuracy over time.[8]
Bias inheritance is another reason why the use of AI requires strong legal oversight. Bias may be defined as “an inclination of temperament or outlook especially a personal and sometimes unreasoned judgement”[9]. Because AI systems generate outputs based on the data they receive, they can reproduce or even intensify existing social biases when the training data itself is biased.[10] In this sense, bias in AI systems may conflict with fundamental constitutional rights such as the right to equality and non discrimination since biased systems can result in unfair or discriminatory treatment.[11]If a system was created with biased input against women for example, such a system will in turn produce outputs or decisions that are discriminatory to women thereby resulting in unconstitutional outcomes.
Furthermore, AI systems operate through what is known as the Black Box system where data is entered and an output is produced but the internal reasoning process remains opaque or unclear. This lack of visibility means that developers and regulators cannot easily trace or understand how a decision was reached which reduces transparency and accountability.[12] When AI systems produce an incorrect, biased or harmful result, it is difficult to assign responsibility because a machine or software cannot be held accountable in the same way a human decision maker can.[13] This black box operation of AI is dangerous in fields such a criminal justice because even if they provide a fair output, because no one can see how the outcome came to be it goes against the principles of natural justice that provides that justice must not only be done but it must also be seen to be done[14] as well as the constitutionally guaranteed right to secure protection of the law and afforded a fair hearing.[15]
Furthermore, according to a study conducted from researchers at Massachusetts Institute of Technology (MIT), reliance on AI caused a decline in cognitive functions and reduction in brain activity[16]. In that study, it discovered that participants who consistently depended on systems such as ChatGPT not only showed a decline in intellectual engagement, but they also became increasingly passive and less inclined to think independently, raising ethical concerns about over dependency on AI and its impact on cognitive development.[17] The results of this study indicate that overuse of AI may erode essential cognitive skills and autonomy and it is therefore imperative that governments and relevant regulatory bodies should adopt measures to discourage excessive reliance on AI tools and to promote continued human intellectual engagement.
Overall, the disadvantages linked to AI reveal serious ethical, social, and legal challenges that cannot be overlooked. These concerns underline the need for clear and robust regulatory frameworks to ensure that AI is developed and used in a manner that protects individuals and upholds fundamental values.
Balancing innovation with Legal Safeguards
Artificial Intelligence is increasingly influencing sectors such as the economy, education, and public administration, making regulatory intervention necessary. in the absence of appropriate legal controls, AI systems may create significant risks while excessive regulation could hinder innovation and national development. It is therefore essential for the state to adopt a balanced regulatory approach that safeguards societal interests without impending technological advancement.
In Zambia, legislative efforts to address emerging digital risks include the Data Protection Act which establishes rules governing the collection, processing, storage, and use of personal data[18] and the Cyber Securities Act which focuses on strengthening cybersecurity frameworks and response mechanisms.[19] Although these statutes contribute to the protection of personal information, they do not adequately regulate the autonomous decision making processes of AI systems and their provisions are often too general to effectively address the complex and evolving nature of artificial intelligence.
To address this gap Zambia must formulate laws in a similar manner to the EU AI Act which is widely regarded as the world’s first comprehensive legal instrument governing AI and this model applies a risk based approach, categorizing AI systems according to the level of risk they pose.[20] Systems deemed to present unacceptable risks are prohibited as these pose a clear threat to fundamental rights, high risk level AI systems are subject to stringent compliance requirements, and lower risks systems are subject to minimal regulation.[21] This structured approach ensures both the protection of fundamental rights and the promotion of innovation.
Accountability remains a critical component of AI systems regulation and where harm arises from AI systems such as inaccurate medical outputs or failures in autonomous technologies, it must be clearly established who bears legal responsibility and effective regulatory frameworks should therefore impose liability and sanctions for misuse. For example, the EU’s AI Act provides for significant administrative penalties for non compliance including substantial fines applicable fines up to 35 000 000 EUR[22]. Article 5(2) of the Act further places responsibility on designated actors or controllers who must demonstrate adherence to regulatory requirements.[23]
Additionally, strong data protection laws must govern how AI systems collect and use personal data and information. Because AI systems depend extensively on large datasets many of which contain sensitive personal data thereby increasing the risk of surveillance, identity theft, unauthorized disclosure, and misuse of private information[24] legal frameworks should mandate informed consent, restrict data collection to what is necessary, and impose stringent penalties for data breaches and individuals should be granted enforceable rights including the right to be informed of any potential privacy violation and have the right to correct or delete their data from AI systems.
In addressing these concerns, Zambia can draw guidance from the Europe’s General Protection Regulation (GDPR) which establishes comprehensive standards for data protection. For instance, Articles 13 and 14 of the GDPR requires transparency by obligating data controllers to inform individuals about the use of their data including the purposes of processing, the logic involved, and the rights available to them.[25] Article 5 also outlines key principles such as data minimisation, purpose limitation, storage limitation, integrity, and confidentiality.[26]
Complementing the GDPR, The European Union’s Artificial Intelligence Act prohibits certain high risk practices including real time biometric surveillance while also requiring transparency, accountability, and human oversight in high risk AI applications.[27] Similarly, Article 35 of the GDPR introduces the requirement for Data Protection Impact Assessments where processing activities especially those involving new technologies that are likely to pose significant risks to individuals rights and freedoms.[28] This provision reinforces the safeguards established under Articles 13 and 14 by ensuring that potential risks are addressed and identified proactively.
In light of these developments, Zambia should consider aligning its domestic legal framework with these international standards, particularly in areas where existing legislation remains underdeveloped. Such alignment would ensure that the advancement of artificial intelligence is balanced with protection of individual privacy rights.
The regulation of artificial intelligence must also address the issue of transparency in decision making processes. Many AI systems operate as “black boxes meaning their internal operations and reasoning are not easily understood or accessible.[29] This lack of transparency raises significant concerns particularly in high stakes areas such as healthcare, criminal justice, and finance. To address this, legal frameworks should require a level of explainbility, ensuring that the outcomes produced by AI systems can be understood and scrutinised.
The European Union’s General Data Protection Regime (GDPR) provides a useful model in this regard. For example, Article 22 establishes that individuals have the right not be subjected to decisions based solely on automated processing.[30] This provision strengthens transparency and accountability by supporting the “right to explain” law whereby individuals are entitled to meaningful information about the logic underlying automated decisions. Similarly, Zambia can adopt the approach in the UNESCO Recommendation on Ethics of Artificial Intelligence which emphasizes that individuals should be informed of the reasons behind decisions made by AI systems[31].
Closely related to transparency is the issue of bias and discrimination. AI systems can unintentionally reproduce or amplify biases embedded in the data in which they are trained and this creates a pressing need for regulatory safeguards to prevent discriminatory outcomes. In order to avoid these biases, Zambian laws must therefore incorporate mechanisms to address algorithmic bias, particularly in areas where such risks are most pronounced by adopting similar legislation enacted by other countries, for example the New York Local Law on automated employment decision tools requires independent bias audits and obliges employers to publish audit summaries on their websites and make them accessible to applicants at least 6 months after results.[32] Such measures promote accountability and help ensure that AI systems do not perpetuate unfair or discriminatory practices.
Safety regulations is a critical component of artificial intelligence governance, particularly in relation to high risk applications such as autonomous vehicles, medical diagnostic systems, and critical infrastructure technologies.[33] Given the potential impact of these systems on human life and public safety, governments should establish rigorous certification procedures before such technologies are deployed and these procedures can mirror existing regulatory models in sectors like aviation and pharmaceuticals where The government should establish certain certification processes, similar to those used in industries like aviation where the EU AI Act mandates assessments for high risk systems before they are introduced to the market to ensure that systems meet the standards relating to cybersecurity, accuracy, robustness and the mitigation of bias.[34] AI systems should be subjected to rigorous pre deployment testing, similar to regulatory approaches adopted by bodies such as the food and drug administration which require clinical evaluation, verification of data quality, and continuous monitoring of medical AI technologies, comparable to the approval processes applied to pharmaceuticals.[35]In addition, continuous monitoring after deployment is essential to ensure ongoing safety and effectiveness. The EU AI Act reinforces this by requiring mechanisms such as logging, incident reporting, and human oversight to track system performance and respond to emerging issues. Likewise, the National Institute of standards and Technology’s AI Risk management Framework (AI RMF) emphasizes the importance of continuous risk assessment and mitigation throughout the lifecycle of AI systems[36].
Conclusion
In conclusion while AI offers considerable benefits, its risks necessitate effective regulation. While international frameworks provide guidance, there is clear need for comprehensive and binding national laws. Rapid growth of AI makes regulation not just optional but essential. The objective should not be to hinder innovation, but to ensure it develops in a controlled manner. Ultimately, as AI becomes increasingly embedded in everyday life, governments must focus on proper regulation to ensure these systems remain accountable and under human oversight.
BIBLIOGRAPHY
Table of Cases
R v Sussex Justices, ex parte McCarthy [1924]
Zambian Legislation
Constitution of Zambia (Amendment) Act No 2 of 2016
Cyber Security Act. No 3 of 2025 (Zambia)
Data Protection Act No 3 of 2021 (Zambia)
Health Practitioners Act No 24 of 2009 (Zambia)
International Legislation
New York City Local Law 144 of 2021 (Automated Employment Decision Tools)
Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 (General Data Protection Regulation) [2016] OJ L119/1
Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 (Artificial Intelligence Act)
Secondary Sources
Andrew R Chow, ‘ChatGPT May Be Eroding Critical Thinking Skills, According to a New MIT Study’ (Time, 17 June 2025) https://time.com/7295195/ai-chatgpt-google-learning-school/ accessed 16 July 2026
Awati R and Yasar K, ‘What Is a Black Box AI?’ (TechTarget, 16 October 2024) https://techtarget.com accessed 16 July 2026
Copeland BJ and Encyclopaedia Britannica, ‘Artificial Intelligence’ (Encyclopaedia Britannica, 2 June 2026) https://www.britannica.com
Coursera, ‘How Does AI Work? Basics to Know’ (15 October 2025) https://www.coursea.org accessed 16 July 2026
EU AI Risk, ‘High-Risk AI System Requirements: Complete Compliance Guide’ (27 August 2025) https://euairisk.com accessed 16 July 2026
FDA, ‘Considerations for the Use of Artificial Intelligence to Support Regulatory Decision Making for Drug and Biological Products’ (Guidance, 30 June 2025)
ICON plc, ‘Understanding FDA Regulations for AI in SAMD’ (24 June 2025) https://www.iconplc.com accessed 16 July 2026
Jenni AI, ‘A Comprehensive Guide to Artificial Intelligence and Machine Learning: What You Need to Know’ (6 November 2023) https://jenni.ai/artificial-intelligence/machine-learning accessed 16 July 2026
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Merriam-Webster, ‘Bias’ https://www.merriam-webster.com/dictionary/bias accessed 16 July 2026
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PMC, ‘Artificial Intelligence in Healthcare’ (2021) https://pmc.ncbi.nlm.nih.gov accessed 16 July 2026
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University of Cincinati, ‘9 Benefits of Artificial Intelligence (AI) in 2026’ https://online.uc.edu accessed 16 July 2026
[1] Encyclopaedia Britannica, ‘Artificial Intelligence (AI)’ (Britannica, ( June 2026) https://www.britannica.com/technology/artificial-intelligence accessed 14 July 2026.
[2] Contentsuare, AI Data Processing: What It Is and Why It Matters’ (Contentsquare, 5 November 2025) https://contentsquare.com/guides/data-processing/ai/ accessed 14 July 2026.
[3] O’Brien Kaaba and Joseph Chirwa, ‘Legal Writing in the Era of Artificial Intelligence’ (UNZALAW Legal Editorial Board, UNZA, MKLT, 13 March 2026).
[4] University of Cincinnati, ‘9 Benefits of Artificial Intelligence (AI) in 2026’ (UC Online, 11 September 2024) https://www.online.uc.edu/blog/artificial-intelligence-ai-benefits.html accessed 14 July 2026.
[5] Constitution of Zambia (Amendment) Act No.2 of 2016, art 17.
[6] Usman, ‘Why AI Models Should Not Train on Sensitive Data’ (Walturn, 16 March 2026) https://www.walturn.com/insights/why-ai-models-should-not-train-on-sensitive-data accessed 14 July 2026.
[7] Coursera, ‘How Does AI Work? Basics to Know’ (Coursera, 8 January 2024) https://www.coursera.org/articles/how-does-ai-work accessed 14 July 2026.
[8] PMC, ‘Artificial Intelligence in Healthcare’ (2021) https://pmc.ncbi.nih.gove/articles/PMC8452365/ accessed 14 July 2026.
[9] Merriam- Webster, ‘Bias’ https://www.merriam-webster.com/dictionary/bias accessed 14 July 2026.
[10] Jenni AI, ‘The History of Artificial Intelligence: From Concept to Reality’ https://jenni.ai/artificial-intelligence/history accessed 14 July 2026.
[11] Constitution of Zambia (Amendment) Act No 2 of 2016, art 23.
[12] Rahul Awati and Kinza Yasar, ‘what is a black box AI?’ TechTarget (16 October 2024) accessed July 16 2026.
[13] Health Practitioners act s71(2) (Act no. 24 of 2009, Laws of Zambia).
[14] R v Sussex Justices, ex parte McCarhy (1924).
[15] Constitution of Zambia (Amendment) Act No 2 of 2016, art 18(1).
[16] Andrew R Chow, ‘ChatGPT May Be Eroding Critical Thinking Skills, According to a New MIT Study’ (Time, 17 June 2025) https://time.com/7295195/ai-chatgpt-google-learning-school/ accessed 16 July 2026.
[17] Ibid.
[18] Data Protection Act No 3 of 2021 (Zambia).
[19] Cyber Security Act Act No.3 of 2025 (Zambia).
[20] Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonized rules on
[21] Ibid.
[22] Regulation (EU) art 99,100.
[23] Ibid.
[24] Jenni AI (n 10).
[25] Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to processing of personal data (General Data Protection Regulation) [2016] OJL119/1.
[26] Ibid.
[27] Regulation (EU) 2024/1689 of the European Parliament and the Council of 13 June 2024 laying down harmonized rules on artificial intelligence (Artificial Intelligence Act).
[28] Regulation (EU) (n 23).
[29] Rahul Awati and Kinza Yasar ‘what is a black box AI? (n 12).
[30] Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data (General Data Protection Regulation) [2016] OJ L119/1.
[31] UNESCO, ‘Recommendation on the Ethics of Artificial Intelligence’ (23 November 2021).
[32] New York City Local Law 144 of 2021 (USA, New York City) (Automated Emplyment Decision Tools).
[33] EU AI Act, art 6 (Classification Rules for High-Risk AI systems).
[34] EU AI Act (Regulations (EU) 2024/1689), annex III; EUAIRisk, ‘High-Risk AI System Requirements: Complete Compliance Guide’ (27 August 2025) https://euairisk.com/resources/eu-ai-act-high-risk-requirements accessed 16 July 2026.
[35] FDA, ‘Considerations for the Use of artificial Intelligence to support Regulatory Decision Making for Drug and Biological Products’ (Guidance, 30 June 2025); ICON plc, ‘Understanding FDA Regulations for AI in SaMD’ (24 June 2025) https://www.iconplc.com/insights/blog/2025/06/24/fda-regulations-ai-medical-devices accessed 16 July 2026.
[36] NIST, ‘AI Risk Management Framework (AI RMF 1.0)’ (2023); EU AI Act, ch 2, s 2 (Post- Market Monitering).
