While regulations are created to protect consumers and markets, they're often complex, making them costly and challenging to adhere to. Highly regulated industries like Financial Services and Life Sciences have to absorb the most significant compliance costs. Deloitte estimates that compliance costs for banks have increased by 60% since the financial crisis of 2008, and the Risk Management Association found that 50% of financial institutions spend 6 to 10% of their revenues on compliance. Artificial intelligence (AI) and intelligent automation processes, such as RPA (robotic process automation) and NLP (natural language processing) can help drive efficiencies up and costs down in meeting regulatory compliance. In a single year, a financial institution may have to process up to 300 million pages of new regulations, disseminated from multiple state, federal, or municipal authorities across a variety of channels.

"Data is the new oil." Originally coined in 2006 by the British mathematician Clive Humby, this phrase is arguably more apt today than it was then, as smartphones rival automobiles for relevance and the technology giants know more about us than we would like to admit. Just as it does for the financial services industry, the hyper-digitization of the economy presents both opportunity and potential peril for financial regulators. On the upside, reams of information are newly within their reach, filled with signals about financial system risks that regulators spend their days trying to understand. The explosion of data sheds light on global money movement, economic trends, customer onboarding decisions, quality of loan underwriting, noncompliance with regulations, financial institutions' efforts to reach the underserved, and much more. Importantly, it also contains the answers to regulators' questions about the risks of new technology itself. Digitization of finance generates novel kinds of hazards and accelerates their development. Problems can flare up between scheduled regulatory examinations and can accumulate imperceptibly beneath the surface of information reflected in traditional reports. Thanks to digitization, regulators today have a chance to gather and analyze much more data and to see much of it in something close to real time. The potential for peril arises from the concern that the regulators' current technology framework lacks the capacity to synthesize the data. The irony is that this flood of information is too much for them to handle.

DISCO, a leader in AI-enabled legal technology, officially opened the doors of its new office in New York City. Located at 335 Madison Avenue next to Grand Central Station, DISCO's New York office provides proximity to leading global law firms, international corporations, and an investor community that increasingly engages DISCO to explore new ways technology can deliver better legal outcomes. We are excited to announce that the doors of our New York office are officially open. With global headquarters in Austin, Texas and EMEA headquarters in London, DISCO is creating footholds in markets that are not only critical locations for the legal industry, but also provide access to top talent. DISCO is aggressively growing its sales, marketing, engineering, professional services, and human resources teams, and will build its New York office to accommodate multiple functions to best meet the needs of employees and customers.

Elastic is a free and open search company that powers enterprise search, observability, and security solutions built on one technology stack that can be deployed anywhere. From finding documents to monitoring infrastructure to hunting for threats, Elastic makes data usable in real-time and at scale. Thousands of organizations worldwide, including Barclays, Cisco, eBay, Fairfax, ING, Goldman Sachs, Microsoft, The Mayo Clinic, NASA, The New York Times, Wikipedia, and Verizon, use Elastic to power mission-critical systems. Founded in 2012, Elastic is a distributed company with Elasticians around the globe. The Machine Learning team is responsible for developing and integrating statistical tools and machine learning models in ElasticSearch and Kibana.

Algorithmic systems – often referred to by the buzzword Artificial Intelligence (AI) – increasingly pervade our daily lives. They are used to detect social benefits fraud, to surveil people at the workplace, or to predict parolees' risk of reoffending. Often, these systems do not only rest on shaky scientific grounds but can be used in ways that infringe people's basic rights – like those to non-discrimination, freedom of expression, privacy, or access to justice –, can undermine foundational democratic principles, and through their non-transparent nature and the lack of accountability mechanisms can be in tension with the rule of law. Against this background and in light of its mandate, the Council of Europe has recognized the need for states to govern the development and use of AI systems. The Council of Europe is an international organization founded in 1949 with the task to uphold human rights, democracy, and the rule of law in Europe.

Last week, the Justice Department announced a newly revised policy for when prosecutors should charge people under the Computer Fraud and Abuse Act, the decades-old, controversial anti-hacking law. Many of the fights around the CFAA have hinged on what is--and is not--illegal hacking: If a mother violates a website's terms of service by creating a social media profile with a photo of someone else and a fake name, for instance, does that qualify? Or if a police officer searches a government license plate database for personal reasons, instead of work reasons, is that hacking? What about if a Major League Baseball team guesses a former employee's password and uses it to download information about his new team? Or a college student tries to find bugs in a voting app as part of an election security course?

In 2020, a machine-learning algorithm helped researchers to develop a potent antibiotic that works against many pathogens (see Nature https://doi.org/ggm2p4; Artificial intelligence (AI) is also being used to aid vaccine development, drug design, materials discovery, space technology and ship design. Within a few years, numerous inventions could involve AI. This is creating one of the biggest threats patent systems have faced. Patent law is based on the assumption that inventors are human; it currently struggles to deal with an inventor that is a machine.

It is utopian to rule out any form of anthropomorphism when addressing a conversational assistant because of the use of language as a vector of exchange. Designers, therefore, must limit these shortcomings with the implementation of these design rules, thus reducing the risks of deception and dependency, and giving confidence in these systems.

Clearview AI has been fined £7.5 million by the UK's privacy watchdog for scraping the online data of citizens without their explicit consent. The controversial facial recognition provider has scraped billions of images of people across the web for its system. Understandably, it caught the attention of regulators and rights groups from around the world. In November 2021, the UK's Information Commissioner's Office (ICO) imposed a potential fine of just over £17 million on Clearview AI. Today's announcement suggests Clearview AI got off relatively lightly.

Artificial Intelligence (AI) Patent Application filings continue their explosive growth trend at the U.S. Patent Office (USPTO).