It takes courage to speak truth to the most powerful technology companies in the world. Timnit Gebru is a truth teller. Gebru was the most senior Black woman to lead a team of AI ethicists at Google, hired to find issues and improve the technology. She was ultimately fired after co-authoring a paper that did just that; it exposed racial discrimination and environmental harm in large-scale artificial intelligence systems at the company. Her ousting sparked protests by scholars and Google employees around the world.

The UK's data protection watchdog has confirmed a penalty for the controversial facial recognition company, Clearview AI -- announcing a fine of just over £7.5 million today for a string of breaches of local privacy laws. The watchdog has also issued an enforcement notice, ordering Clearview to stop obtaining and using the personal data of UK residents that is publicly available on the internet; and telling it to delete the information of UK residents from its systems. The US company has amassed a database of 20 billion facial images by scraping data off the public internet, such as from social media services, to create an online database that it uses to power an AI-based identity-matching service which it sells to entities such as law enforcement. The problem is Clearview has never asked individuals whether it can use their selfies for that. And in many countries it has been found in breach of privacy laws.

The American Bar Association has taken greater notice of emotional AI as a tool for honing courtroom and marketing performance. It is not clear if the storied group has caught up with the controversy that follows the comparatively new field. On the association's May 18 Legal Rebels podcast, ABA Journal legal affairs writer Victor Li speaks with the CEO of software startup EmotionTrac (a subsidiary of mobile ad tech firm Jinglz) about how an app first designed for the advertising industry reportedly has been adopted by dozens of attorneys. Aaron Itzkowitz is at pains to make clear the difference between facial recognition and affect recognition. At the moment, the use of face biometrics by governments is a growing controversy, and Li would like to stay separate from that debate.

Clearview AI has been fined £7.55 million ($9.5 million) by the UK's privacy watchdog for illegally scraping the facial images of UK residents from social media and the web. It was also ordered to stop obtaining the data of UK residents and to delete any it has already collected. "The company not only enables identification of those people, but effectively monitors their behavior and offers it as a commercial service. That is unacceptable," said UK information commissioner John Edwards in a statement. The UK's Information Commissioner's Office (ICO) opened a joint investigation with Australia into Clearview AI back in 2020, and issued a preliminary fine of £17 million ($21.4 million) against the company late last year.

On April 21, the EU officially proposed the Artificial Intelligence Act, outlining the ability to monitor, regulate and ban uses of machine learning technology. The goal, according to officials, is to invest in and accelerate the use of AI in the EU, bolstering the economy while also ensuring consistency, addressing global challenges and establishing trust with human users. AI use cases with unacceptable risk will be banned outright. High-risk applications, similarly, pose a high risk to health, safety and fundamental rights, though the debate around the definition of "high risk" has been raging since last year, with more than 300 organizations weighing in. These AI applications are allowed on the market only if certain safeguards are in place, such as human oversight, transparency and traceability.

Developments in the field of artificial intelligence (AI) are moving quickly. The EU is working hard to establish rules around AI and to determine which systems are welcome and which are not. But how does the EU do this when the biggest players, the US and China, often have different ethical views? Political economist Daniel Mügge and his team will conduct research into how the EU conducts its'AI diplomacy' and will sketch potential future scenarios. "Our research is essentially about regulation around AI", says political economist Daniel Mügge.

A recent study has used machine learning analysis techniques to chart the readability, usefulness, length and complexity of more than 50,000 privacy policies on popular websites in a period covering 25 years from 1996 to 2021. The research concludes that the average reader would need to devote 400 hours of'annual reading time' (more than an hour a day) in order to penetrate the growing word counts, obfuscating language and vague language use that characterize the modern privacy policies of some of the most-frequented websites. 'The average policy length has almost doubled in the last ten years, with 2159 words in March 2011 and 4191 words in March 2021, and almost quadrupled since 2000 (1146 words).' The mean word count and sentence count among the corpus studied, over a 25 year period. Though the rate of increase in length spiked when the GDPR and the California Consumer Privacy Act (CCPA) protections came into force, the paper discounts these variations as'small effect sizes' which appear to be insignificant against the broader long-term trend.

From the coining of the term back in the 1950's to now, AI has taken remarkable leaps forward and only continues to grow in relevance and sophistication But despite these advancements, there's one problem that continues to plague AI technology – the internal bias and prejudice of its human creators. The issue of AI bias cannot be brushed under the carpet, given the potential detrimental effects it can have. A recent survey showed that 36% of respondents reported that their businesses suffered from AI bias in at least one algorithm, resulting in unequal treatment of users based on race, gender, sexual orientation, religion or age. These instances incurred a direct commercial impact: of those respondents, two-thirds reported that as a result they lost revenue (62%), customers (61%), or employees (43%). And 35% incurred legal fees because of lawsuits or legal action.

Not a day goes by without reports of a new achievement, investment or national plan powered by artificial intelligence. AI is embedded in many of the apps and the software we use, and it is making functions such as voice interaction a reality. Yet the adoption of AI itself is largely absent from most of the organisations with which we directly interact or work. While applications that were just a dream only a few years ago are now widespread, their development is still restricted to a handful of savvy companies. For instance, Meta (formerly Facebook) is building the world's largest supercomputer.

"Quality is never an accident. It is always the result of intelligent effort" – John Ruskin The adoption of artificial intelligence (AI) is gathering pace. And with a significant level of adoption in emerging markets, the trend has seen an increase in almost every industry, encompassing a range of business sectors from production, through marketing and sales to HR and risk management. Alongside this trend, companies are broadening their focus to include stakeholders beyond their shareholders. This can be attributed to a variety of factors.