Online freedom and safety

Basics

Find out whether using the tool could expose people to state or non-state control of the internet, or to abuse online. This covers three things. First, whether governments or armed groups cut off networks or power, and when src-031 p5. Second, censorship and surveillance: who owns the networks and who can read what passes over them src-032 p11; src-031 p5. Third, online abuse, especially technology-facilitated gender-based violence (TFGBV): harm done or made worse through digital tools, which falls mostly on women and girls src-014 pp16-17. Laws on free speech and privacy matter, but they may not be upheld in practice src-031 p5.

Why it matters for AI tools

A tool can put its users at risk. Data that would be harmless in one place can be dangerous in the wrong hands in another, and some groups face extra surveillance, for example activists or LGBTQ people whose location data could expose them src-032 p11. Even where the risk of interception is low, people may avoid a channel they fear is watched, or one linked to a political or religious group src-032 p11. An AI tool might also be used, by the organisation or by others, to support censorship, disinformation or surveillance of vulnerable people src-011 pp7-8. Principles for Digital Development lists digital repression through surveillance and censorship among the main harms of digital work, and notes these harms are less understood for AI src-010 p10.

Access to the tool itself can be cut. A provider may block users in some countries, or be banned or sanctioned by a government the project works under src-011 pp7-8.

Online abuse also shapes who uses a tool. Fear of abuse leads many women to censor themselves or withdraw from online services src-014 p18. In some places, norms limit women's phone use partly out of fear for their reputation; in others, women use phones freely but meet harassment src-019 p7.

What good evidence looks like

• A record of network or power shutdowns in the area, who ordered them, and around which events src-031 pp5-6.
• Who owns and controls the networks and main channels, and whether any are tied to political or religious groups src-031 p5; src-032 p11.
• Laws on free speech, privacy and data, and evidence on whether they are enforced src-031 p5.
• Whether any user group faces extra surveillance, and what data it would be dangerous to collect from them src-032 p11.
• Whether users change or hold back what they send because they worry who might read it src-032 p18.
• Local evidence on online abuse, broken down by gender, using the terms each audience uses src-014 pp14-16; src-019 p7.
• For an AI provider: whether it restricts access from the countries of use, what happens if it is banned or sanctioned, and whether it has ties to military or intelligence agencies src-011 pp7-8.
• A plan to review the risks when the context changes, for example if censorship rises src-037 p27; src-039 p21.

How to find out

Desk research on conflict history, censorship, free speech and privacy law, and who runs the networks src-031 p5. Key informant interviews with officials, to test whether laws and policies hold in practice src-031 p5. Focus groups with community members, and short survey questions on whether network or power access is ever cut and why src-031 pp5-6. Focus groups and interviews on whether fear of being read changes what people send src-032 p18. A risk assessment combined with a data protection impact assessment (a formal review of how a project's use of personal data could harm people), repeated when the context changes src-037 p27.

Limits and disagreements

Only one source addresses AI directly, and it is a checklist for organisations choosing tools, not a study src-011 pp7-8. Principles for Digital Development says AI harms in this area are less understood src-010 p10. None of the sources reports a case of an AI tool affected by a shutdown or by surveillance.

The guidance on shutdowns and surveillance comes from SIMLab's 2018 framework and its example assessment, so it is one voice (src-032, src-031). The example is a community policing project across 12 countries src-031 p4.

Evidence on online harms is thin and mostly from high-income settings src-019 p7. The figures in the IREX guide come from Kenya and are cited without method details src-014 p18.

Sources differ on anonymity. Girl Effect notes it can lower risk to girls on some platforms and has increased trolling of girls and women on others src-037 p38. Projects need to judge this for each channel.

Practitioner detail

Groups in Kenya name the same harms differently. Donors and international NGOs say TFGBV; some local groups say online gender-based violence; survivors and support services name tactics such as cyberstalking or doxxing; police and courts use the terms in Kenya's cybercrime and ICT laws src-014 pp14-16. Research on online harms should check which words each audience uses.

Laws on paper may give a route to redress without being enforced well. Kenya's Computer Misuse and Cybercrimes Act 2018 covers cyber harassment and the sharing of intimate images, but IREX notes that enforcing it in practice can be hard src-014 p46.

The IREX guide lists forms of TFGBV, including harassment, image-based abuse such as deepfakes, cyberstalking and doxxing (publishing someone's private details) src-014 pp15, 17. Abuse often moves from online to offline src-014 p16.