Can AI Research Be Stopped? No, But it Should Become More Open, Democratic and Scientific

Can AI research stop even temporarily? In my view, no, as AI is the response of humanity to a global society and physical world of ever-increasing complexity. As the physical and social complexity increases processes are very deep and seem relentless, AI and citizen morphosis are our only hope to have a smooth transition from the current Information Society to a Knowledge Society. Else, we may face a catastrophic social implosion.

Maybe we reached the limits of AI research being engineered primarily by Big Tech companies, while treating powerful AI systems (like LLMs) almost as marvelous black boxes, whose functionality (the why?) is very poorly understood, both due to lack of access to technical details and due to the huge AI system complexity. Naturally, this lack of knowledge and related confusion as to the nature of human and machine intelligence entails very serious social risks.

It seems that the Open Letter reflects both welcomed genuine concerns on the social risks as well as financial concerns on risk management related, e.g., to future AI investments or the possibility of massive expensive lawsuits (in an unregulated and un-legislated environment) in case things go wrong.

However, I doubt if the proposal for a six-month ban on large-scale experiments is the solution. It is impractical for geopolitical reasons and can bring too few benefits, particularly if LLM training is targeted, rather than LLM deployment.

Furthermore, the melodramatic tone of this Open Letter can only enhance technophobia in the wider population.

On the other hand, scientific views discounting LLM value (e.g., like the ones expressed by Chomsky) are old-fashioned (reminiscent of perceptron rejection by Minsky and Papert) and not productive either.

Of course, AI research can and should become different: more open, democratic and scientific.

Here is a proposed list of points to this end:

  • The first word on important AI research issues that have a far-reaching social impact should be delegated to elected Parliaments and Governments, rather than to corporations or individual scientists.
  • Every effort should be made to facilitate the exploration of the positive aspects of AI in social and financial progress and to minimize its negative aspects.
  • The positive impact of AI systems can greatly outweigh their negative aspects if proper regulatory measures are taken. Technophobia is neither justified nor a solution.
  • In my view, the biggest current threat comes from the fact that such AI systems can remotely deceive Too many commoners that have little (or average) education and/or little investigative capacity. This can be extremely dangerous to democracy and any form of socio-economic progress.
  • In the near future, we should counter the big threat coming from LLM and/or CAN use it in illegal activities (cheating in University exams is a rather benign use in the space of the related criminal possibilities).
  • Their impact on labor and markets will be very positive, in the medium-long run.
  • In view of the above, AI systems should: a) be required by international law to be registered in an ‘AI system register’, and b) notify their users that they converse with or use the results of an AI system.
  • As AI systems have a huge societal impact, and towards maximizing benefit and socio-economic progress, advanced key AI system technologies should become open.
  • AI-related data should be (at least partially) democratized, again towards maximizing benefit and socio-economic progress.
  • Proper strong financial compensation schemes must be foreseen for AI technology champions to compensate for any profit loss, due to the fore-said open-ness and to ensure strong future investments in AI R&D (e.g., through technology patenting, obligatory licensing schemes).
  • The AI research balance between Academia and Industry should be rethought to maximize research output while maintaining competitiveness and granting rewards for undertaken R&D risks.
  • Education practices should be revisited at all education levels to maximize the benefit of AI technologies while creating a new breed of creative and adaptable citizens and (AI) scientists.
  • Proper AI regulatory/supervision/funding mechanisms should be created and beefed up to ensure the above.

Several such points were already discussed in the 2021 AI Mellontology workshop and are also included in Prof. Pitas recent book on ‘AI Science and Society’.

Hot this week

Mitsubishi Electric Europe launches browser-based production analytics app to simplify shopfloor visibility

Mitsubishi Electric Europe B.V. has launched DataNavigateApp, a browser-based production analytics solution designed...

Software Improvement Group publishes State of Software 2026

Software Improvement Group (SIG) has published the State of...

Gaia-X Welcomes the EU Cloud and AI Development Act and Calls for a Practical Trusted Path to European Digital Sovereignty

Gaia-X welcomes the European Commission’s proposed Cloud and AI...

The Accountability Gap in AI: Who Is Responsible When Systems Act Autonomously?

There is a line in IBM training material from...

Mitsubishi Electric Europe launches browser-based production analytics app to simplify shopfloor visibility

Mitsubishi Electric Europe B.V. has launched DataNavigateApp, a browser-based production analytics solution designed...

Software Improvement Group publishes State of Software 2026

Software Improvement Group (SIG) has published the State of...

Donaldson Launches Smart Monitoring System for Industrial Gases and Hydraulic Fluids Filtration

Donaldson, a global leader in technology-led filtration products and...

OnLogic to Showcase Practical Physical AI and Full-Facility Workload Consolidation at Automate 2026

Industrial computing and edge solution specialists, OnLogic (www.onlogic.com), has...

Festo Launches GripperAI Software to Simplify Flexible Robot Handling

Festo has introduced GripperAI, an AI-powered software solution that...

Related Articles

Popular Categories