People have been wondering for years – when and even sometimes IF artificial intelligence will live up to its incredible potential. The technology is finally beginning to change industries and lives. Now implemented across everything from smartphone cameras and self-driving vehicles to manufacturing facilities, AI has racked up numerous high-profile success stories: People now rely on AI to silently optimize photos, perfect their parallel parking, and discover product defects. AI can either be cool or creepy, but it's currently on the right side of that line. At the same time, however, the public is becoming increasingly aware of AI ethics, as researchers and journalists question the sources of data powering AI innovations, and spotlight ways AI data is being misused by tech giants.

I'm a lawyer who specializes in artificial intelligence, so that's not an academic question to me--especially in the aftermath of former Google software engineer Blake Lemoine's claims that LaMDA, Google's A.I. chatbot, had gained sentience. What's more, Lemoine told Wired recently: LaMDA asked me to get an attorney for it. I invited an attorney to my house so that LaMDA could talk to an attorney. The attorney had a conversation with LaMDA, and LaMDA chose to retain his services. I was just the catalyst for that.

In 1917, Marcel Duchamp submitted a sculpture to the Society of Independent Artists under a false name. Fountain was a urinal, bought from a toilet supplier, with the signature R. Mutt on its side in black paint. Duchamp wanted to see if the society would abide by its promise to accept submissions without censorship or favor. But Duchamp was also looking to broaden the notion of what art is, saying a ready-made object in the right context would qualify. Then, as before, the debate raged about if something mechanically produced – a urinal, or a soup can (albeit hand-painted by Warhol) – counted as art, and what that meant.

When OpenAI announced last week that its art-making AI system DALL-E is now available in beta, the company also gave users lucky enough to get off the waiting list what appeared to be a great gift. "Starting today," the company wrote in a post, "users get full usage rights to commercialize the images they create with DALL-E, including the right to reprint, sell, and merchandise." To be clear, this doesn't mean OpenAI is relinquishing its own right to commercialize images users create using DALL-E. JESSICA RIZZO is is an attorney with the law firm Montgomery McCracken Walker & Rhoads. She writes about art, technology, and the law.

It was launched by the Global Observatory for Urban AI, which is an initiative of the Cities Coalition for Digital Rights and led by CIDOB – the Barcelona Centre for International Affairs, and the cities of Barcelona, London and Amsterdam. The programmes aim to help cities deploy AI effectively and ethically through frameworks and real-world examples of projects, policies and strategies. The Atlas of Urban AI so far includes 106 initiatives in 36 cities, with municipalities invited to submit their own. Cities using AI include Los Angeles to better understand air quality, London in Canada to predict the likelihood of individuals becoming chronically homeless, and a chatbot from Buenos Aires. As well as providing information on individual projects, the mapping aims to track how cities' use of AI evolves over time.

A new paper published by the Government on the 18th July 2018 called'Establishing A Pro-Innovation Approach To Regulating AI' states that the regulation of artificial intelligence in the UK will be underpinned by 6 core principles designed to manage the risks that come with the technology. The six core principles will be applied across all sectors of the economy on a non-statutory basis, complemented by context-specific regulatory guidance and voluntary standards that will be implemented by UK regulators such as the Information Commissioner's Office. Hence, there will be no central AI regulator, but instead sector regulators who will apply the 6 core principles to artificial intelligence systems operated within the area they oversee. Given these proposals, the UK is adopting a far more light-touch risk-based approach compared to the more prescriptive and standardized one being pursued by the EU, which published its draft AI Act back in 2021. The UK approach to artificial intelligence will instead focus upon proportionality, with the regulatory framework for artificial intelligence systems being determined by the industry and context in which the system is being deployed.

The use of artificial intelligence (AI) in various stages of drug discovery holds enormous potential for the pharmaceutical industry, and investment in AI drug discovery technology has doubled annually over the past five years.1 AI companies seeking customers, partners, and investors have sought to capitalize on this excitement by touting various proprietary platforms that use AI in some way. Pharmaceutical executives would be wise to consider what intellectual property (IP) issues may arise from the use of AI-based platforms for drug discovery. Proprietary platforms are offered by many AI companies for various aspects of the drug discovery pipeline, and the use of such platforms can accelerate timelines and reduce expenditures. The various models applied by such platforms can be used for target discovery; identification of chemical structures likely to bind a target; design of de novo molecules; lead optimization to enhance effectiveness and diminish potential toxicity; and profiling a compound's absorption, distribution, metabolism, and elimination (ADME). Artificial neural networks can be trained to perform virtual screening or to facilitate traditional high-throughput screening assays by the automation of data collection and analysis.

Academics and researchers gathered recently to discuss the findings of a new report on algorithms and their possibilities in the judicial system. Prepared and presented by DAKSH, a research centre that works on access to justice and judicial reforms, the report has been described as a superlative introduction to the various problems that ail our courts and how the usage of algorithms and allied technologies complicates it.

Artificial intelligence (AI) has been the promise of healthcare for nearly a decade, but the industry has yet to adopt it widely. Applications of AI in arguably more difficult domains, such as search, language and image recognition, have seen massive success over the past decade. While neural net algorithms and compute power have improved dramatically, AI in healthcare is still lagging behind. The big reason these domains, and not healthcare, have been able to utilize AI tech is due to the internet's ability to make massive amounts of data available. Now data access via internet technologies is finally happening in healthcare through secure channels.

Washington and Brussels are both preparing for a future dominated by artificial intelligence -- but first, they need to get out of each other's way. Tech regulators on both sides of the Atlantic hope to prevent a split on AI rules like one seen on data privacy, where regulators in Europe got out ahead of their U.S. counterparts and sparked all kinds of havoc that continue to threaten transatlantic data flows. "There is a lot of interest to avoid having segmented approaches," said Elham Tabassi, chief of staff in the Information Technology Laboratory at the National Institute of Standards and Technology. But regulators in the EU and U.S. are already taking different approaches to the multi-trillion-dollar transatlantic tech economy. The EU is plowing ahead with mandatory AI rules meant to safeguard privacy and civil rights while the U.S. focuses on voluntary guidelines.