Bridging the AI divide: access as a human right

The AI divide is the digital divide extended to artificial intelligence: gaps in access, in the skills to use AI and check its output, and in the benefits people obtain, plus a new gap between those who understand automated systems and those merely processed by them. Human rights law already bears on who gets to use AI and on what terms, and a few design and policy choices will largely decide whether AI narrows social gaps or widens them.

What the AI divide is

Researchers often distinguish three layers of the digital divide:

• Access to connectivity and devices.
• The skills and confidence to use them.
• The benefits people obtain, such as a better job or a resolved problem.

AI adds a layer to each. The most capable models run in data centers, need a reliable connection and are usually sold by subscription or metered use. Language models learn mostly from text, so languages with little digitized text get weaker results and more errors, which users who cannot read a dominant language have fewer ways to notice. Using AI well also takes skills that are rarely taught: framing a task, checking an output, knowing when not to trust it. AI also increasingly sits on the other side of the counter, screening and ranking people, which divides those who understand such systems from those merely processed by them.

Why the rights framing matters

The roots of this framing are older than today’s AI systems. The Universal Declaration of Human Rights (Article 27) and the International Covenant on Economic, Social and Cultural Rights (Article 15) recognize everyone’s right to share in the benefits of scientific progress. The UN Convention on the Rights of Persons with Disabilities (Article 9) obliges states to ensure equal access to information and communications technologies, and the European Pillar of Social Rights lists digital communications among the essential services everyone should be able to access.

Together they point to a principle: once a technology is the gateway to education, work, health or public administration, exclusion from it is a public concern, not a private inconvenience. In practice the right is less “a chatbot for everyone” than a set of guarantees: no one loses an essential service because it was automated, no one is treated worse by an automated system because of who they are, and everyone can reach a person and contest a decision that affects them. The GDPR (Article 22) already provides the last of these for decisions based solely on automated processing with legal or similarly significant effects.

How AI can widen the gap

Consider a bank that closes branches and moves first-line support to an AI assistant in its app. For a customer with a recent phone, good eyesight and fluency in the national language, service improves. For an older customer who relied on the branch, it removes the only channel they could use; the fallback, if any, is a queue. Or take automated screening of job applications: candidates who know how screeners read a résumé adapt; equally qualified candidates who do not may be filtered out before a human reads a word.

Price works more quietly. Free versions of AI services are often limited in capability, and their terms may allow users’ inputs to be used for training, while private, higher-quality access costs money. Those with the least money tend to pay with their data and get the weaker product.

How AI can narrow the gap

The same technology can also remove barriers older tools could not. Speech recognition and image description give people with visual or motor impairments access to text and surroundings. Machine translation lets a parent who does not speak the school’s language read a letter from the teacher. Smaller models on ordinary hardware can work offline where connectivity is poor, at the cost of some capability. Libraries and community centers can offer both a connection and someone to ask.

Each gain is conditional: on accessibility built in from the start, not patched in later; on translation that is reliable and can be verified; and on staff trained to support users rather than simply offering a terminal.

Choices that decide the outcome

Whether AI widens or narrows the divide follows mostly from decisions by those who deploy it and those who set the rules, not from the technology itself.

• Teach AI literacy broadly, in schools, adult education and workplaces, not only to specialists.
• Keep a human channel for every essential service that adopts AI, without penalty for using it.
• Build accessibility and language coverage in from the start, and test with the people concerned.
• Measure outcomes by age, disability, language and place, not only the number of users.
• Keep decisions that gate credit, work, housing or benefits reviewable by a person.

Some already have legal anchors in Europe. Since 2 February 2025, Article 4 of the EU AI Act has required providers and deployers of AI systems to attend to the AI literacy of their staff; in 2026 the digital omnibus on AI (Regulation (EU) 2026/1744) rephrased that duty from ensuring a sufficient level of AI literacy to taking measures that support it. The European Accessibility Act has applied to many digital products and services since 28 June 2025. These set a floor, not a ceiling. Each carries a cost in money, time or data; the point is to weigh those costs openly, before the people affected have given up.

A practical takeaway

Readers who teach, run a service or decide on a procurement need not settle whether access to AI is a freestanding right. It is enough to ask three things of any deployment: who cannot use the system and what happens to them; what using it costs the person in money, data and attention; and whether the person can reach a human and contest the result. If a deployment has no good answer to one of them, the divide it creates is a choice, and a reversible one.

The Foundation researches digital inclusion and responsible AI; its technical report, Bias Detection Under Article 4a of the EU AI Act, examines when synthetic, anonymized or differentially private data is enough to test an automated system for discrimination.

In short

The AI divide is the digital divide extended to artificial intelligence: gaps in access, in the skills to use AI and check its output, and in the benefits people obtain. It also adds a gap between those who understand automated systems and those merely processed by them. A few design and policy choices will largely decide whether AI narrows or widens these gaps.

Frequently asked questions

What are the three layers of the digital divide?

Researchers often distinguish three layers of the digital divide: access to connectivity and devices, the skills and confidence to use them, and the benefits people obtain, such as a better job or a resolved problem. AI adds a layer to each of these three.

Why do AI tools work worse in some languages?

Language models learn mostly from text, so languages with little digitized text get weaker results and more errors. Users who cannot read a dominant language have fewer ways to notice those errors.

Is access to AI a human right?

The Universal Declaration of Human Rights (Article 27) and the International Covenant on Economic, Social and Cultural Rights (Article 15) recognize everyone’s right to share in the benefits of scientific progress. In practice the right is less a chatbot for everyone than a set of guarantees: no one loses an essential service because it was automated, and everyone can reach a person and contest a decision.

Which EU rules already address AI literacy and accessibility?

Since 2 February 2025, Article 4 of the EU AI Act has required providers and deployers of AI systems to attend to the AI literacy of their staff. In 2026 the digital omnibus on AI (Regulation (EU) 2026/1744) rephrased that duty to taking measures that support it. The European Accessibility Act has applied to many digital products and services since 28 June 2025.

What can organizations do to keep AI from widening social gaps?

Organizations can teach AI literacy broadly, keep a human channel for every essential service that adopts AI without penalty for using it, build in accessibility and language coverage from the start, and measure outcomes by age, disability, language and place. Decisions that gate credit, work, housing or benefits should stay reviewable by a person.

How to cite LASTHUMAN Foundation. (2026, July 7). Bridging the AI divide: access as a human right. https://lasthuman.today/insights/bridging-the-ai-divide.html