AI Disclosure Day: What Is AI Revealing About Us?

The recent arrival of Disclosure Day (https://www.disclosuredaymovie.com/watch-more) inspired an interesting thought.

The concept of disclosure is pretty straightforward. Hidden things become revealed. Ignored issues become obvious. Unspoken assumptions become questioned. For decades, films used the notion of disclosure to examine major shifts in human perception.

Whatever it was about – space exploration, government secrets, scientific discoveries, technological progress – the essence of the question was always the same: What happens when people discover something that changes their perception of reality?

Now, artificial intelligence seems to create its own disclosure moment. Not because AI is hidden. AI is ubiquitous. AI is everywhere – in headlines, in boardrooms, at conferences, in classrooms, in software solutions, and in government strategies.

But perhaps the real disclosure is something else entirely. AI reveals something that was there long before it appeared. Organisations initiate their AI programmes expecting to discover something new. Instead, they often discover something ancient:

• Bad data quality.

• Fragmented knowledge.

• Lack of ownership.

• Duplication of effort.

• Contradictory processes.

AI did not create all these issues. AI merely makes them more visible.

This may be the first AI disclosure. The technology does not only generate outputs. The technology exposes organisational realities.

Organisations could continue operating without documented processes, isolated knowledge, inconsistent data, and unclear roles. Human adaptability often masked all these problems. People knew whom to contact. Employees knew the workarounds. Managers were using their experience and personal connections. People constantly adapted around the problem, so it stayed hidden.

AI does not forgive this kind of behaviour. When organisations try to implement AI solutions at scale, all these problems become apparent. Suddenly, many questions arise.

• Whom does the data belong to? 

• Who owns it?

• What is the correct version?

• Who is authorised to make decisions?

• Who is responsible when the AI recommendations affect the outcome?

All these questions existed before AI. They just did not require any clear answers. AI forces these questions.

The second AI disclosure concerns knowledge. Organisations often believe that their knowledge is documented and available. AI solutions frequently show that it is not true. Expertise can be available only in the heads of selected individuals. Documented processes can rely heavily on personal experience, judgement, and informal procedures. When the organisation tries to develop its AI solution, it often discovers how much of its knowledge remains invisible.

The issue here is not in the intelligence of the machine. The issue is the dependence on human expertise. The third AI disclosure concerns authority.

Discussions of AI usually focus on the capabilities of the technology. Far fewer discussions touch upon control. With AI becoming involved in recommendation, evaluation, approval, risk assessment, and strategic analysis, organisations must ask themselves a fundamental question. Whom should we ask?

• The technology can recommend.

• The technology can analyse things.

• The technology can predict.

•  The technology can prioritise.

But the responsibility remains human.

However, the problem is that many organisations have never clarified the issues of control, accountability, and decision-making in an AI-powered world. This observation extends beyond individual organisations. Governments, regulators, public institutions, and critical infrastructure operators face the same questions.

• Who controls the system?

• Who verifies the results?

• Who takes responsibility for any mistake?

• Who keeps control when intelligent systems are integrated into core operations?

These are the questions of governance rather than technology. And perhaps this is why many AI discussions look incomplete. 

Public discourse focuses mostly on models, tools, and innovation. But the deeper disclosure touches upon the structures. that:

• govern decision-making.

• manage knowledge.

• allocate authority.

• create resilience.

In this sense, AI may keep the future as it is. AI may reveal the realities that existed already but remained mostly hidden. The most important AI disclosure may not be in what AI tells us about technology. The most important AI disclosure may be in what AI tells us about ourselves. About the organisations we have built and institutions we have created. assumptions we made and weaknesses we overlooked.

Perhaps we do not have to wait for some profound revelation to understand the significance of AI. The disclosure has been taking place all along. The question is, are we ready to see it?

Thanks to Linda Restrepo for her inspiration, too!

( Ps: watch