ASSESSING KENYA’S ARTIFICIAL INTELLIGENCE
REGULATORY FRAMEWORK: NAVIGATING CHALLENGES IN ALGORITHMIC CONTENT MODERATION
AND SYSTEMIC BIAS IN SOCIAL MEDIA PLATFORMS
Illustration
by Gemini AI.[i]
Article by
Maxwell Otieno.
1. INTRODUCTION
The rapid
diffusion of artificial intelligence (AI) across social media platforms has
transformed how information is produced, distributed, and consumed, with
profound implications for democratic discourse, human rights, and equality. As
such, regulation of AI-driven algorithms has become a defining feature of
contemporary governance due to the pervasiveness of data-driven analytics
across social and political life.[1]
The Data
Protection Act No. 24 of 2019, the Computer Misuse and Cybercrimes Act No. 5 of
2018, and the National Artificial Intelligence Strategy (2025–2030) together
signal a national commitment to regulating the digital domain and promoting
innovation. However, the existing regulatory and legal frameworks meant to
address the unique challenges AI technologies pose (namely, algorithmic content
moderation and systemic bias) are inadequate. Without coherent guidelines and
frameworks, AI development might outpace the ability to govern it effectively,
leading to potential misuse and harm.[2]
The deployment
of recommender systems and automated moderation tools has produced a class of
distributed and continuous opaque harms[3]
that traditional actor-centered legal frameworks struggle to capture. At the
same time, structural constraints exacerbate Kenya’s ability to oversee
transnational platforms whose infrastructural capacities far outstrip domestic
regulators. These dynamics generate legal and institutional uncertainty for
platforms, users, and oversight bodies, complicating the attribution of
responsibility and the design of effective accountability mechanisms.
2. REGULATORY SCOPE AND GAPS OF KENYA’S EXISTING
LEGAL AND POLICY INSTRUMENTS
Data
Protection Act (2019)
The Act’s protective power is
significant but inherently circumscribed by its focus on identifiable personal
data, leaving a regulatory void where algorithmic harms intersect with
collective discourse. This inadequacy is most evident in cases where AI moderation
systems do not merely "process" data but characterize it.
Many
algorithmic harms on social media occur through inferred data—where an
algorithm assigns a "harmful" attribute to a user’s post based on
aggregate trends.[4]
Because these inferences often bypass the threshold of "identifiable"
information[5] under
Sections 2 and 35 of the DPA, the DPA offers
an inadequate remedial framework for algorithmic censorship. The DPA does not explicitly regulate
the accuracy of algorithmic interpretation outside of individual profiling that
produces "legal effects," it thus remains a blunt instrument.
With regards
to systemic bias, the statute regulates the data, but not the model. It lacks
explicit provisions requiring bias audits, representativeness of training
datasets, or mandatory reporting of disparate-impact metrics. Hence, systemic
bias is treated indirectly and primarily as a privacy-risk or individual-harms
problem rather than a structural algorithmic governance issue.
Computer
Misuse and Cybercrimes Act (2018)
The CMCA
contains no express provisions addressing algorithmic moderation design,
explainability, or bias. Sections criminalizing unauthorized interference with
systems[6]
or fraud[7]
could, in theory, apply to malicious technical manipulation of moderation
tools, but they do not govern legitimate platform design choices that produce
biased outcomes.
Consequently,
systemic bias arising from algorithmic ranking/moderation sits outside the
CMCA’s primary scope except where bias amounts to a legally cognizable offence
(e.g., fraud, discrimination under separate laws) and can be linked to culpable
misconduct.
Kenya National
AI Strategy (2025–2030)
The National
AI Strategy is a policy roadmap. Its substantive value is normative and
programmatic rather than legal. The Strategy foregrounds fairness, mitigation
of bias, and inclusive datasets; it explicitly identifies bias as a priority
risk[8].
It notes that there are significant concerns about the ethical use of AI,
including issues of bias, discrimination, perpetuation of existing
inequalities, and potential exploitation for surveillance and other invasive
purposes.[9]
It advocates the creation of multi-stakeholder governance bodies (AI
councils/directorates)[10],
and sandboxes for testing moderation tools[11].
3. SOCIO-ETHICAL AND LEGAL IMPACTS OF
ALGORITHMIC CONTENT MODERATION AND SYSTEMIC BIAS ON SOCIAL MEDIA PLATFORMS IN
KENYA
Meareg & 2 others v Meta
Platforms, Inc.
Professor
Meareg Amare, was a well-known and widely respected Tigrayan member of staff at
Bahir Dar University and lived in the city of Bahir Dar for several years. On 9
October 2021, an anonymously run Facebook page called “BDU Staff”, with over
50,000 followers, posted his picture, announcing he was “hiding” at Bahir Dar
University where he was working as a chemistry professor and had carried out
“abuses”.[12]
In the
comments, people called for violence against the professor, calling him a
“snake” and suggesting that he posed a risk to people from the Amhara ethnic
group.[13]
On 3 November 2021 (three weeks after the posts appeared on the BDU staff page)
a group of men followed Meareg home from the university where he taught and
shot him in the legs and the chest outside of his home.[14]
As a result, a
petition was filed at the High Court of Kenya, alleging that the
killing occurred after Facebook posts doxed the professor, revealed his home
address, and incited violence against him, which Meta failed to remove despite
repeated reports. They
argued that the respondent’s Facebook algorithm recommended content that
amounts to propaganda for war, incitement to violence to the Facebook users in
Kenya. They also accused the respondent of granting preferential treatment to
users in other countries as opposed to Facebook users in Africa thus is
discriminative.
The brutal
murder of Professor Meareg Amare serves as a harrowing testament to the
real-world consequences of algorithmic moderation. When automated systems
prioritize engagement over safety and systemic bias leaves non-English speaking
populations vulnerable to automated disinformation, the limitations of
self-regulation become undeniable. Consequently, this elicits an urgent
necessity to investigate the efficacy of Kenya's AI regulatory framework.
CONCLUSION
To
address gaps and mitigate impacts, Kenya should do a number of things. First,
it ought to adopt a risk-based, multi-tiered approach. This involves the
classification of social media AI systems based on the level of risk they pose.
A comprehensive list of recommendations derived from comparative best practices
as well as the theoretical underpinnings of this new legal phenomenon is
provided in Part 2 of this document. It is imperative that Kenya strategically
positions itself as a hub for AI development and adoption. However, this must
be preceded by the establishment of robust legal safeguards.
[1]
Andrea Mennicken and Karen
Yeung, Algorithmic Regulation (CARR Discussion Paper No 68, Centre for
Analysis of Risk and Regulation 2015).
[2]
Ministry
of Information, Communications and the Digital Economy, ‘Kenya National
Artificial Intelligence (AI) Strategy 2025–2030’ (2025)
https://www.ict.go.ke/kenyas-artificial-intelligence-ai-strategy-2025-2030-launched-kicc-nairobi
accessed 8 February 2026
[4]
‘A Right to Reasonable
Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI’
(2019) 2019(2) Columbia Business Law Review 494, 494–620
[5]
ibid
[6]
Computer Misuse and Cybercrimes Act 2018, s 14.
[7]
Computer Misuse and Cybercrimes Act 2018, s 16.
[8]
MICDE (n 2) ch 4
[9]
MICDE
(n 2) ch 4.
[10]
MICDE (n 2) ch 5.
[11]
MICDE (n 2) ch 3.
[12]
NBC
News, “Facebook hit with $2 billion lawsuit connected to political violence in
Africa”, 14 December 2022,
https://www.nbcnews.com/tech/misinformation/facebook-lawsuit-africa-content-moderation-violence-rcna61530
[13]
Time,
“New lawsuit accuses Facebook of contributing to deaths from ethnic violence in
Ethiopia”, 14 December 2022,
https://time.com/6240993/facebook-meta-ethiopia-lawsuit/; NBC News, “Facebook
hit with $2 billion lawsuit connected to political violence in Africa”, 14
December 2022,
https://www.nbcnews.com/tech/misinformation/facebook-lawsuit-africa-content-moderation-violence
rcna61530
[14]
Foxglove, “Death by design:
a major new case against Facebook”, 14 December 2022,
https://www.foxglove.org.uk/2022/12/14/death by-design-major-new-case-facebook/
[i] 'Create an image that suits this topic: ASSESSING KENYA’S ARTIFICIAL
INTELLIGENCE REGULATORY FRAMEWORK: NAVIGATING CHALLENGES IN ALGORITHMIC CONTENT
MODERATION AND SYSTEMIC BIAS IN SOCIAL MEDIA PLATFORMS' (Gemini, Gemini 3 Flash
Image version, Google, 24 March 2026) https://gemini.google.com accessed 25 March 2026.
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