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Meena Alnajar is an��IPilogue��Writer, IP Innovation Clinic Fellow,��and a 2L JD Candidate at��Osgoode��Hall Law School

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Artificial Intelligence (AI) has become both a friend and a foe to our society. , a collection of algorithms, beat Jeopardy! champions and may soon become your next doctor. But AI can also be exploited to . Should we move to ban AI altogether or create more regulations and rules? Ryan Abbott, ��and�� posits in his latest book, , that a different approach to law, not increasing the quantity of laws, is needed to regulate AI. Abbott proposes a new guiding tenet to AI regulation: . This tenet outlines that the law should not discriminate between AI and human behaviour. As AI increasingly invades spaces previously held for people, AI will need to be treated more like people. Abbott examines this concept in four legal areas: tax, torts, criminal, and intellectual property law.

Abbott frames each legal area in the context of growing automation, known as the . The book begins by discussing the changes to our tax regime if more work becomes automated. As an employee, AI does not require the same health benefits and protection. Therefore, businesses will have a tax incentive to automate. As we automate more work, the tax base shrinks, costing governments billions of dollars in tax revenue. To prevent such loss, between people and AI may be the solution. If there is no tax advantage to automated businesses and we move towards guaranteed income so that human employees are not disadvantaged because of AI’s inability to pay taxes, a neutral system for AI in the workplace can be achieved. Additional debates surrounding AI and unemployment currently exist. Some contest that the while others point to the potential negative impacts of AI in the workplace. While automation does generate new jobs in the information sector, those jobs are not easily accessible. Jobs created as a result of the proliferation of AI technology will require extensive education and are often . Increasing automation could create further disparities in the workplace.

The section on intellectual property (IP) is particularly intriguing in light of recent events. On July 29, 2021 . Dr. Stephen Thaler’s AI system ‘DABUS’ was listed as an inventor for a patent related to beverage packaging and emergency lights. On July 30, 2021, Australia followed suit and , stating their decision to be The patenting process, as Abbott predicted in this book, may need to be drastically changed to recognize AI as an inventor. Patent Offices have not yet issued guidance as to whether AI could be regarded as an inventor. To be , an invention must be new, useful, and inventive, otherwise known as . The standards for patentability may be raised if AI is allowed as an inventor.

The person of ‘average skill’ is unclear with AI as an inventor. For instance, if AI becomes part of the biomedical field, responsible for discovering and patenting antibodies, does AI become the person of average skill in biomedicine? Considering that , humans filing to patent a “non-obvious” invention may face significant challenges. If inventive AI is allowed to patent and does so at a faster and greater capacity than humans, could this discourage the spirit of inventorship patent law seeks to foster in our society? Especially given that under AI legal neutrality, AI and humans should not be assessed through different standards. Abbott suggests the contrary: . AI legal neutrality suggests that work generated by AI be treated no less important than work patentable by humans.[1] Further, allowing AI to be listed as an inventor provides more transparency and accuracy to a patent’s creation,[2]ensuring fairness amongst innovators. AI’s capabilities as inventor should be recognized and encouraged since are to our benefit.

A future where AI invents and outperforms humans seems inevitable. Rather than ban a future dominated by AI, humans should view AI as a means to improve on what we have already built . Technology can be dangerous when used for nefarious purposes. However, when regulated within a proper framework, AI promotes ingenuity, saves lives and eases hardships in our society. It is still within our control as legal scholars, lawyers, and leaders to create productive rules so that we can flourish alongside the reasonable, helpful robot as opposed to living in fear of AI’s growing capabilities.

[1] Ryan Abbott, The Reasonable Robot, (Cambridge: Cambridge University Press, 2020) at 164 (Kobo eBook).

[2] Ibid at 165.

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Ryan Abbott is Professor of Law and Health Sciences at the University of Surrey School of Law and Adjunct Assistant Professor of Medicine at the David Geffen School of Medicine at UCLA.

The past few years have witnessed some astounding advances in artificial intelligence, with high profile breakthroughs, such as software now in use , , and . As AI continues to improve, it is going to take over an ever-increasing number of tasks that were once only performed by people. This is going to have profound consequences socially, economically, and legally.

explores the legal implications of AI stepping into the shoes of people and doing human sorts of tasks. It finds that laws written with people in mind often give an unintentional preference to either human or AI activity. In turn, this tends to result in negative and unintended outcomes. The Reasonable Robot proposes that the solution to this problem is for the law not to discriminate between AI and human behavior—a principle of AI legal neutrality. This will ultimately result in more benefits for people.

To illustrate, consider how the law taxes activity by a person and a machine differently. Take the example of the AI used in health care for diagnosis mentioned briefly above. The FDA authorized an autonomous that provides point of care assessment for certain eye diseases. If a hospital or medical group needs to hire a human eye doctor to evaluate emergency room patients, in addition to what they have to pay the doctor, they need to pay additional payroll taxes to the government based on the doctor’s wages. However, if the hospital or medical group can use the AI system instead of the human doctor, it does not have to pay any payroll taxes. As a result, if the person and the AI cost about the same and generate a similar level of productivity (often a complex, or at least not a 1:1, comparison), businesses will be incentivized to automate to save on taxes. In addition to avoiding payroll taxes, automation has other tax benefits, such as accelerated tax depreciation.

The gist of this is that the tax system is not neutral between human and AI activity, and the law pushes businesses to automate—even if it is only to save on taxes. The solution to this problem is to eliminate human-centric employment taxes to level the playing field. This will help ensure that businesses are only automating when it results in genuine efficiencies.

To take another example, AI has been generating creative and inventive output for years that, if that output had been made by a person, would be protected by intellectual property rights. However, the United States has not clarified whether a creative work made without a traditional human author, or an invention generated without a traditional human inventor, could receive copyright or patent protection. That is going to be a major problem if AI-generated works become a major source of commercially valuable creative content or socially valuable innovations, because it will mean that the right incentives will not be in place for people to make, use, and develop AI that can generate socially valuable outputs.

The Reasonable Robot argues that the solution to this problem is to ensure IP protection for AI-generated works, with the owner of the AI as the owner of the AI’s output. As with the tax solution above, this would level the playing field and allow businesses to generate creative output or innovate using either people or AI when one or the other (or both), is more effective.

This argument is being put into practice with (AIP) which involves a series of legal test cases brought in various jurisdictions to obtain protection for AI-generated inventions without a traditional human inventor. The AIP recently obtained the for an AI-generated invention in South Africa, as well as a holding that an AI-generated invention is patentable. Litigation is currently ongoing on these patents in the United States, United Kingdom, EPO (Europe), and Germany.

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