Algorithm Conference
February 18 - 20, 2021
UTD - Dallas, TX
Should an AI be recognized as an inventor?
AI as inventor?
It is internationally accepted that a patent can only be granted to a human. But in the age of AI, if such a system invents something without directions from the human that wrote it, who should be recognized as the real inventor? The AI system? The human that wrote it? Or no patent may be issued.
That is the question facing patent authorities and lawmakers in Europe, Israel, UK, and the US, after Professor Ryan Abbott and colleagues filed two patent applications on behalf of Dabus AI, an AI system written by Dr Stephen Thaler.
Researchers, companies and developers who are increasingly turning to AI systems for business and commercial purposes are keeping a close watch on the outcome of the patent applications.
The patent applications have recentyl being denied by the UK Intellectual Property Office (UKIPO) and the US Patent and Trademark Office (USPTO). But according to this BBC report, the efforts of Prof Abbott and Dr Thaler has prompted the World Intellectual Property Organisation to start a “consultation on [the] issue and is due to continue the discussion at a session [later this year], with the outcome expected to influence future IP policy.”
Both Prof Abbott and Dr Thaler are confirmed to speak during Algorithm Conference, an opportunity to hear directly from the key people involved in the status quo-challenging patent applications. So if you haven’t purchased your ticket yet, you may do so by clicking here.
Key players
Stephen Thaler, PhD
President/CEO, Imagination Engines
Dr Thaler is the author of more than two dozen patents on generative AI. DABUS, his newest patent, is the focus of a global legal effort to credit AIs as inventors of the IP they create, and the basis for this WSJ article (paywall, but archived here).
A 15-year veteran of aerospace giant McDonnell Douglas, his work for the military includes novel electro-optical materials discovery as well as brilliant robotic control systems capable of self-originating Machiavellian tactics on the battlefield.
He has authored numerous papers based upon his patented neural network paradigms to model cognition, consciousness, and sentience. In the first of these works, Thaler offered highly controversial models of hallucination within the traumatized brain.
More recently he has suggested a compelling perspective on the close relationship between psychopathologies and creativity. Now, he has received a patent for a neural network methodology that allows scale up of connectionist architectures to trillions of computational neurons in order to create free-thinking, sentient synthetic entities.
Keynote: DABUS, The sentient algorithm
Two patent-worthy inventions have been autonomously conceived by machine intelligence. Unfortunately, examiners have rejected them as patents since they lack a “natural person” as their author.
The irony of these decisions is that the extensive generative neural system responsible for these notions, DABUS, is arguably conscious and sentient, the key features believed to distinguish humans from many other terrestrial life forms, as well as from the much larger inorganic world.
But DABUS is built upon the human plan, since it develops feelings for whatever it may be attentive to, either in its external environment or within its imagination. In this way, it savors its discoveries and inventions. Thus, it can develop a ‘first person’, subjective feel for its own cognition, the criterion philosophers typically use to disqualify computer algorithms as conscious.
Now functioning as an artificial inventor, DABUS can relish its self-originated concepts, in much the same way it can appreciate its non-seminal cognition, all the while inventing heightened significance to itself.
Herein, the case is made that DABUS, apart from other forms of generative AI, has attained the purest form of personhood, one without extraneous corporeal features and functions.
Key takeaways:
1. A brief description of the previous patents DABUS is built upon.
2. A high-level description of DABUS and how it works.
3. The computational approach used by DABUS to generate subjective feelings.
4. A description of how DABUS harnesses its feelings to generate ideas and interpret its world.
5. The correspondence between DABUS and human consciousness.
6. Accounts of how DABUS can misbehave, and why that isn’t so bad.
Ryan Abbott, PhD
Professor of Law and Health Sciences
Ryan Abbott, MD, JD, MTOM, PhD, is Professor of Law and Health Sciences at the University of Surrey School of Law, Adjunct Assistant Professor of Medicine at the David Geffen School of Medicine at UCLA, Partner at Brown, Neri, Smith & Khan, LLP, and a mediator and arbitrator with JAMS.
He has consulted for, among others, the UK Parliament, European Commission, WHO, and the World Intellectual Property Organization. He is a licensed physician and patent attorney in the United States, and a non-practicing solicitor in England and Wales. Managing Intellectual Property magazine named him one of the 50 most influential people in intellectual property in 2019.
Working with Dr Thaler, Prof Abbott’s efforts to win recognition for DABUS AI machine as an inventor has drawn coverage by the WSJ, the BBC, CMS Law-Now, among others. He is the author of The Reasonable Robot: Artificial Intelligence and the Law.
He will give you a firsthand account of what it’s being like to try and win recognition for AI machines as inventors.
Keynote: TBA
Discussion panel
As an extra, the speakers listed above, plus a couple more yet to be announced, will participate in a discussion panel titled Should an AI system be recognized as an inventor. Regardless of where you stand on whether an AI can be sentient and creative, you’ll want to hang around for this discussion panel.
Register
Registration for workshop and for the conference itself is now open. The workshop has a limited number of tickets, so hurry and register if you want to guarantee yourself a spot. To reserve your ticket(s), click on that big red button.
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al-Khwārizmī -> algoritmi -> algorithm
