A Proposal for Credit Assignment — Concerning the U.K. Goverment’s consultation on Copyright and Artificial Intelligence

The training of A.I. and machine learning models is, in the technical vocabulary of the field, a problem of credit assignment [1]. The entire achievement of a machine learning training algorithm lies in accurately tracing the myriad miniscule connections — assigning credit — to those features of the input data responsible for achieving each output target in its training data and targets.

It would be ironic then if, tasked with assigning credit to their inputs for their outputs, A.I. modellers should baulk and call that too daunting a challenge.

It is not necessary to achieve a great degree of accuracy, or timeliness or even consistency in assigning credit to content creators and IP holders whose property has been used to train models. A little effort to provide something that is half accurate most of the time would be a helpful start.

It is not necessary to invent a new compensation model, or a new process for registering the interests and contact details of IP owners. The music industry designed and implemented solutions for this problem over a century ago. Without the aid of A.I. Or a computer.

There is such a thing as legalized robbery. For instance, loan sharking used to be legal, but it was still robbery even when it was legal. We prefer to make such things illegal because it is wrong to let those with the will to do so to take advantage of people over whom they have an advantage of, for instance, physical strength.

In commerce, strength is largely financial, partly political. The bigger, better-connected company is immensely more powerful than the individual content creator. Just as with SLAPP cases and with libel laws, the legal battle is too one-sided to even contemplate.

The UK consultation on IP and A.I. provides a unique opportunity to develop and implement a far better vision. The relationship between A.I. developers and IP holders can and should be a positive, mutually beneficial, symbiotic relationship.

A.I. certainly depends, utterly, on IP creators. If the A.I. developer monetizes whilst the IP holder is left with nothing that would be parasitic and destructive[2], not symbiotic. If an algorithm and system is implemented to reasonably share with IP holders fair recompense for their works' contribution to A.I. output, the relationship could be symbiotic, mutually beneficial, and even a virtuous circle of increasing benefit to both. Not to mention the rest of us.

[1] https://www.google.com/search?q=back+propagation+as+an+algorithm+for+credit+assignment

[2] https://www.inet.ox.ac.uk/news/new-study-reveals-impact-of-chatgpt-on-public-knowledge-sharing

The Argument For Machine Consciousness

The modern argument for machine consciousness can be paraphrased as follows:

  1. We know lots about how electro-mechanical systems work.

Therefore:

  1. Let us believe that consciousness is also an electro-mechanical system (because if it is, then we will be able to understand it).

Therefore:

  1. Machines can be conscious

One can sympathise with giving belief (2) a research budget. But to confidently assert that conceivable consequences of (2) – such as (3) – are facts about the world, is bluster. Writing bluster into our legal and moral thinking would be a mistake.

I suppose the motivation for (2) is, we always want to believe we can understand things. And, impatiently, we also want to believe things can be understood well enough just with the current state of our knowledge, insights and tools.

But gung-ho optimism based on unevidenced confidence does not have a good record and can do more harm than good.

At the current time, the negative I hope we can avoid is:

Large corporations will use stories about machine consciousness and machine legal status to transfer legal risk away from themselves, making it easier for them to prioritise profitable machinery over human lives.

A example will be when a corporation denies legal liability for a robot or self-driving car which injures a passer-by, by saying it was the robot's fault, not theirs.

A better, more logical, move in the early 21st century would be to first acknowledge that

  1. The current state of our knowledge, tools and insights does not suffice to understand what consciousness is or how it works.