Victor Schwartz is a partner in the Washington, D.C. office of the Kansas City-based law firm of Shook, Hardy & Bacon L.L.P. He chairs the firm's Public Policy Group, which seeks to be the vanguard of developing public policy issues that will help improve the civil justice system. Mr. Schwartz has been an advisor for each of the American Law Institute's (ALI) Restatement (Third) of Torts projects: Products Liability, Apportionment of Liability, and Liability for Physical and Emotional Harm. He is a life member of the ALI. Prior to entering the full time practice of law, Mr. Schwartz was a professor and dean at the University of Cincinnati College of Law.
A recent issue of a popular computing journal asked which laws would apply if a self-driving car killed a pedestrian. This paper considers the question of legal liability for artificially intelligent computer systems. It discusses whether criminal liability could ever apply; to whom it might apply; and, under civil law, whether an AI program is a product that is subject to product design legislation or a service to which the tort of negligence applies. The issue of sales warranties is also considered. A discussion of some of the practical limitations that AI systems are subject to is also included.
Greta Cutulenco, Co-founder and CEO says, "Vehicles are becoming more complex - both mechanically and electronically. This rise in complexity creates a strain on testing processes, which gives rise to quality issues, and eventually a spike in warranty claims and recalls. Acerta offers a SaaS platform that uses machine learning to provide real-time malfunction detection and failure prediction. The platform learns the normal behaviour of the tested system and the complex correlations between data streams, and automatically detects anomalies in real-time. This enables manufacturers to utilise all of the data they collect to produce accurate insight into their system quality."
In July 2015, Google's public-relations machine was in full-on crisis mode. Earlier that year, the search giant announced Photos, an AI-driven app that used machine-learning to automatically tag and organize your pictures based on the people, places and things depicted in them. It was an exciting step forward, but Photos wasn't perfect.
Data Nuggets in the Stream A retailer may do 100,000 POS credit card transactions per day. Opening more registers as soon as checkout volume starts to trend upwards makes customers happy. It may not be long until we have good enough AI (or at least pseudo-AI), and good enough voice recognition to replace human customer service workers, but right now nothing beats a knowledgeable employee with the authority to actually make things right for a customer who has gotten a defective product or poor service of some sort. If you're doing high-frequency stock buying and selling, making hundreds or thousands of trades per minute (or even per second in some cases), you must be able to process data and make decisions - or have a program that makes decisions - fast enough that the length of your connection to the stock exchange can make a noticeable difference in your profits -- which is pretty darn fast.
A California-based startup called Instrumental developed an intelligent AI inspection system to help manufactures identify product defects on the assembly line. Instrumental makes a hardware box that goes on the assembly line and takes a photo of every device that passes through and they recently announced their deep learning software called Detect which highlights units that appear defective or anomalous, giving our customers a significant edge in discovering and resolving product issues. Using TITAN X GPUs and cuDNN with the TensorFlow deep learning framework, they are able to process hundreds of units in seconds and identify the most interesting units to review. According to their blog, an engineer using Detect remotely caught an assembly process issue still in progress on the line and was able to inform the factory to correct it right away.
"We recently introduced AI claims handling … and saved 40,000 work hours, while speeding up the claim processing time to five seconds," Tom de Swaan told Reuters, after the insurer started using machines in March to review paperwork, such as medical reports. "We absolutely plan to expand the use of this type of AI (artificial intelligence)," he said. De Swaan said Zurich Insurance, Europe's fifth-biggest insurer, would increasingly use machine learning, or AI, for handling claims. De Swaan said he does not fear competition from tech giants like Google-parent Alphabet or Apple entering the insurance market, although some technology companies have expressed interest in cooperating with Zurich.
"We recently introduced AI claims handling ... and saved 40,000 work hours, while speeding up the claim processing time to five seconds," Tom de Swaan said, after the insurer started using machines in March to review paperwork, such as medical reports. De Swaan said Zurich Insurance, Europe's fifth-biggest insurer, would increasingly use machine learning, or AI, for handling claims. De Swaan said he does not fear competition from tech giants like Google-parent Alphabet or Apple entering the insurance market, although some technology companies have expressed interest in cooperating with Zurich. "None of the technology companies so far have taken insurance risk on their balance sheet, because they don't want to be regulated," he said.
Zurich Insurance is introducing artificial intelligence to help decide personal injury claims. The insurance giant is rolling out the technology after processing time was cut from an hour to only seconds during a trial, according to a Reuters report. "We recently introduced AI claims handling … and saved 40,000 work hours, while speeding up the claim processing time to five seconds," Zurich chairman Tom de Swaan told Reuters. De Swaan said that Zurich would continue to increase the role of AI in claims handling.