The UK's data regulator has issued a warning to tech companies about protecting personal information when developing and deploying large language, generative AI models. Less than a week after Italy's data privacy regulator banned ChatGPT over alleged privacy violations, the Information Commission's Office (ICO) published a blog post reminding organizations that data protection laws still apply when the personal information being processed comes from publicly accessible sources. "Organisations developing or using generative AI should be considering their data protection obligations from the outset, taking a data protection by design and by default approach," said Stephen Almond, the ICO's director of technology and innovation, in the post. Almond also said that, for organizations processing personal data for the purpose of developing generative AI, there are various questions they should ask themselves, centering on: what their lawful basis for processing personal data is; how they can mitigate security risks; and how they will respond to individual rights requests. "There really can be no excuse for getting the privacy implications of generative AI wrong," Almond said, adding that ChatGPT itself recently told him that "generative AI, like any other technology, has the potential to pose risks to data privacy if not used responsibly."

AI regulations are coming and will be a significant focus for lawmakers in the U.S. and globally in 2022. That's according to Beena Ammanath, executive director of the Global Deloitte AI Institute, who sees a fast-moving worldwide push for AI regulation. As artificial intelligence technology use increases across enterprises, Ammanath said it will be important for governments, the private sector and consumer groups to develop regulations for AI and other emerging technologies. Broadly, advocates for AI regulation seek transparency for black box algorithms and the means to protect consumers from bias and discrimination. The U.S. has been slow to regulate AI compared to the U.K., Germany, China and Canada.

Even as so many enterprises are still struggling to move their artificial intelligence and machine learning pilots into production, there's another challenge on the horizon. How can organizations ensure that their algorithms are acting in a responsible and ethical fashion? For those that don't figure this out, the results can cause embarrassment at best and potentially cause your company to run afoul of the law at worst. Those looking for guidelines and help with this question got some answers from Frank Buytendijk, vice president and analyst at research and consulting firm Gartner, during the session Artificial Intelligence and Ethics: What You Need To Do Today at Gartner IT Symposium this month. It used to be that artificial intelligence was touted as the solution that would ultimately eliminate bias and ethics problems.

Facial recognition software that struggles to see black faces. A risk assessment algorithm with embedded racial biases. While artificial intelligence promises efficiency, and will likely determine which company wins market leadership, the technology also has an ugly side. Human hands can transfer prejudice onto the algorithms they create. But AI products don't become bias-infused at random, analysts and executives say.

New technologies continue to shape society, albeit at an accelerating rate. Decades ago, societal change lagged behind tech innovation by many years, a decade or more. Now, change is occurring much faster as evidenced by the impact of disrupters including Uber and Airbnb. Central to much of the change is the data being collected, stored and analyzed for various reasons, not all of which are transparent. As the pace of technology innovation and tech-driven societal change accelerate, businesses are wise to think harder about the longer-term impacts of what they're doing, both good and bad. Technology in all its forms is just a tool that can be used for good or evil.