ISO 42001 Annex A.5.5: Examine Wider Societal Impacts of AI

What control A.5.5 requires in practice

Control A.5.5 asks the organisation to assess and record how its AI systems could affect society, across their whole life cycle. It widens the lens from named users and groups to the wider environment in which a system operates. The control does not tell the organisation how far its responsibility extends; it expects a reasoned assessment relevant to the system and its use. Annex B, as guidance, offers examples of areas where effects may be beneficial or harmful: environmental sustainability, economic matters such as access to services and employment, government and public institutions, health and safety, and norms, traditions, culture and values. It also invites the organisation to consider how its systems could be misused, how they could reinforce historical bias, and how their computing demands relate to its own sustainability goals. Outputs are an assessment and a record of conclusions and the reasoning behind them.

Describe a plausible wider consequence

Annex B.5.5 discusses beneficial and adverse effects across environmental, economic, health, governance and cultural contexts. It also addresses misuse and the possibility of reinforcing historical patterns. The guidance must be considered through clause 6.1.3(e), while B.1 permits a context-specific implementation.

As an original method, trace how repeated or widespread use could affect a wider system. Distinguish a plausible pathway supported by evidence from a remote speculation. The organisation should recognise limits in its knowledge and influence without using them as a reason to ignore a relevant effect.

Why assessing societal impact of AI matters

Societal effects can feel remote from daily business until they become the subject of public concern, legislation or customer procurement rules. An organisation that has already thought about how widespread use of its systems could affect the environment, the labour market or public trust is better placed to respond, and often to avoid the problem altogether. This assessment also surfaces opportunities, such as services that widen access or reduce waste. Public bodies and large buyers increasingly ask suppliers about these effects, so a documented, accurate assessment supports tenders and due diligence. It protects the organisation from the opposite error as well: claiming broad benefits that nobody has examined, which invites scepticism.

How to implement control A.5.5

Keep the assessment tied to plausible pathways, not abstract concern, and be accurate about the limits of what you know. Proportion matters here too: you cannot study every conceivable effect, so concentrate on those that are plausible, significant and connected to your own influence.

1. Describe the system, its scale of use and the wider settings it touches, such as communities, markets or institutions.
2. Review the areas Annex B suggests and mark those with a plausible link to your system.
3. For each, trace how repeated or widespread use could produce a benefit or harm, and note the evidence for that pathway.
4. Consider misuse by others and the risk that the system reinforces existing patterns of disadvantage.
5. Relate computing demands and resource use to your own sustainability goals where relevant.
6. Separate well-supported conclusions from uncertainty, and record who was consulted.
7. Feed the findings into design, risk treatment and communication, and revisit them as use grows.

Illustrative manufacturing example: savings and resource demands coexist

Illustrative software example: repeated misleading information

A software company offers AI-generated summaries of public technical information. Individual errors may seem small, but repeated distribution of an unsupported claim through many customer channels can affect wider understanding and trust.

The assessment examines how content is checked, corrected and redistributed, including foreseeable misuse of authoritative-looking summaries. It considers the organisation's contribution and available controls without claiming responsibility for every downstream statement. A disclaimer alone may be inadequate if the design encourages uncritical redistribution.

Consider scale, context and distribution

A use that is limited in one setting can have different effects when widely adopted. Examine the reach of outputs, the decisions they influence and whether many organisations rely on similar assumptions. Relevant expertise can help where societal pathways are difficult to evaluate.

Benefits and adverse effects may fall on different groups or appear over different periods. Avoid collapsing them into a single favourable score without explanation. Equally, do not assume that a speculative adverse scenario proves that a beneficial use must stop. The assessment should support proportionate, informed decisions.

Include misuse and historical conditions

Foreseeable misuse can change societal effects even when intended use is benign. Consider how features or outputs might be repurposed in a way relevant to the organisation's role. Keep the discussion at a governance level and connect it with suitable restrictions, information or monitoring where justified.

Existing data and practices can carry historical patterns into a system. Examine the relevant context rather than presume that automated outputs are neutral because they are generated consistently. This connects with data quality and impacts on individuals and groups.

Evidence and useful boundaries

Common nonconformities with A.5.5

Weaknesses typically appear where the assessment is generic or disconnected from decisions.

• The record states that the system benefits society without examining any specific pathway or the possibility of harm.
• Only positive effects were described, with no consideration of misuse, bias reinforcement or resource demands.
• The assessment was never revisited although the scale or purpose of use changed materially.
• No evidence shows that anyone with relevant knowledge outside the project team contributed.
• Conclusions exist but did not influence design, risk treatment or communication with interested parties.