Dr. Lance B. Eliot is a world-renowned expert on Artificial Intelligence (AI) with over 6.8+ million amassed views of his AI columns. As a seasoned executive and high-tech entrepreneur, he combines practical industry experience with deep academic research.
In today’s column, I am going to showcase and discuss the key findings of a Center for Law, Science, and Innovation workshop undertaken by the Arizona State University Sandra Day O’Connor College of Law that took place in Washington D.C. and was entitled “Soft Law Governance of AI Applications” . Attendees consisted of esteemed speakers along with carefully chosen commentators who offered insightful remarks and spurred spirited thoughtful discussion and debate on the topics being covered.
Before I jump into unpacking the details of the nine papers, let’s make sure we are all on the same page when it comes to the nature of both AI soft laws and the likes of AI hard laws. Think of AI laws all told and immediately grab hold of both the venerated AI hard laws and the vital AI soft laws. Don’t let AI soft laws be like the Maytag repairman who used to sit around and be all alone.The workshop began with opening remarks by Professor Gary Marchant and then a succinct foundational overview of soft laws and hard laws associated with autonomous vehicles was provided by David Bonelli .
In this paper, the role of communication is noted as essential for how autonomous vehicles will interact with humans that are on or near our roadways. Communication modes and means are an important element and absolutely essential for the overall acceptance and safety of AVs on our public streets and open highways.
Here’s what that means. Envision that self-driving cars are roaming constantly throughout your community. These AVs are video recording whatever they happen upon. If you stitched together this voluminous digital data, you could pretty much glean a lot of monetizable information. Real estate agents might be willing to pay to find out which homes in a given neighborhood might be ready for going onto the market.
I am a big proponent of trying to find analogous settings that can inform and reveal underpinnings for gauging what and where the AV industry might be heading. A compelling case is made that indeed the soft law evolutionary impacts on amusement parks can spur ideas and conventions for coping with the emergence of AVs.
Providing yet another indication of the value of soft law, the author emphasizes that neurotechnology as a fast-advancing and ever-changing technology requires the readiness and adaptability of soft law. I fully agree. Furthermore, the paper notes that not enough is being done on the soft law front for neurotechnology. I again agree with this. We must push harder to ensure that soft law gets a profoundly needed seat at the governance table in this space.
As noted, there are times when the acquiring firm has strongly held soft law precepts and is going to want to drive those fervently into the being acquired firm. If the startup has no particular soft law interests, this probably works out suitably, and the deal proceeds. If the startup also has soft law beliefs, there is then a reconciliation process that takes place. Often, since both parties are already up-to-speed on soft law considerations, they can iron out whatever differences might exist.
This paper highlights again the importance of soft law when it comes to the governance of AI. In addition, the authors tackle a now visibly discussed question of whether there ought to be some form of overarching global AI governance body that would engage in these matters on a multinational basis.
When discussing ethical, legal, and social issues , there are a number of rather thought-provoking concerns that emerge with the advent of c-BCI. Here’s a doozy for you. If a c-BCI could potentially read your mind, including capturing your thinking processes, would this be a capability that we want our government to be able to undertake? Some might say that well, this is nothing out of the ordinary and you can either consent to this or not.
Some key recommendations for the FDA are that a greater reliance on transparency ought to be observed, along with the need for heightened AI explainability. The paper further suggests that there be expanded enforcement discretion and reliance on best practices. Included in the set of recommendations is the vital nature of pilot programs and sandboxing. There is also a call for expanded educational and literacy facets when it comes to healthcare, especially medical devices and AI.
In prior days of AI advancement, there was said to have been a focus on being AI-centric, meaning that the attention by AI makers and AI developers was primarily on getting the AI to function. The human impacts were said to be secondary, or maybe not given any attention at all. Those pesky humans, who needs them anyway?
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