Fintech company Klarna, which powers e-commerce transactions for some of the world’s most recognizable brands, including Expedia, Macy’s and Nike, is at the forefront of AI adoption. It has integrated artificial intelligence across the company, most notably with an AI chatbot that it recently said does the equivalent work of 700 customer service agents. Klarna, which employs roughly 4,000 people, recently released statistics that show how efficient and effective the tool has been, wading into the thick of sensitive and high-stakes debates about the role of generative AI in business, how humans interact with it and its implications for the future of work. CEO Sebastian Siemiatkowski explains why he is so transparent about AI’s capabilities, and what concerns him most about the new technology. This interview has been edited for length and clarity. — Read More

There was one individual Olympic spot left. According to the intricate set of rules governing who gets slots for the games, it would come down to who placed highest in the high bar final: Croatia’s Tin Srbić or Brazil’s Arthur Nory Mariano.

They were at the 2023 World Championships in Antwerp, Belgium, last October. Mariano went first. He fell during his routine, giving Srbić some wiggle room. He didn’t need it, though: Srbić completed a clean routine, with Tkachev connections and a double-twisting double layout that he stuck cold; at the end of his routine, he pumped his fists in the air in celebration. He’d qualified for the 2024 Paris Olympics. 

But when his score came in—a 14.500—Srbić thought the judges had made a mistake, one that could cost him a medal at Worlds. He needed to decide if he wanted to make a challenge.  

… These championships were the first time the technology, formally known as the Judging Support System, or JSS, had been used on every apparatus in a gymnastics competition—and its first use in a competition that could make or break an athlete’s Olympic dreams. While the AI judging system did not replace human judges—rather, it was available to help judges review routines in case of an inquiry or a “blocked score”—it still marked a watershed moment for the sport that was years in the making.  — Read More

“How can we affect education for the better?” In this thought-provoking AI Talk, Jonny Gilmore, CEO of Ai8, explains the transformative potential of human:machine teams in the education to career value chain. Ai8 aims to redefine the entire system of education, training, employment, and upskilling, making it more bespoke, affordable, and accessible. — Read More

#augmented-intelligence

Verifiability is a core content policy of Wikipedia: claims need to be backed by citations. Maintaining and improving the quality of Wikipedia references is an important challenge and there is a pressing need for better tools to assist humans in this effort. We show that the process of improving references can be tackled with the help of artificial intelligence (AI) powered by an information retrieval system and a language model. This neural-network-based system, which we call SIDE, can identify Wikipedia citations that are unlikely to support their claims, and subsequently recommend better ones from the web. We train this model on existing Wikipedia references, therefore learning from the contributions and combined wisdom of thousands of Wikipedia editors. Using crowdsourcing, we observe that for the top 10% most likely citations to be tagged as unverifiable by our system, humans prefer our system’s suggested alternatives compared with the originally cited reference 70% of the time. To validate the applicability of our system, we built a demo to engage with the English-speaking Wikipedia community and find that SIDE’s first citation recommendation is preferred twice as often as the existing Wikipedia citation for the same top 10% most likely unverifiable claims according to SIDE. Our results indicate that an AI-based system could be used, in tandem with humans, to improve the verifiability of Wikipedia. — Read More

#augmented-intelligence

We use GPT-4 for content policy development and content moderation decisions, enabling more consistent labeling, a faster feedback loop for policy refinement, and less involvement from human moderators.

Content moderation plays a crucial role in sustaining the health of digital platforms. A content moderation system using GPT-4 results in much faster iteration on policy changes, reducing the cycle from months to hours. GPT-4 is also able to interpret rules and nuances in long content policy documentation and adapt instantly to policy updates, resulting in more consistent labeling. We believe this offers a more positive vision of the future of digital platforms, where AI can help moderate online traffic according to platform-specific policy and relieve the mental burden of a large number of human moderators. Anyone with OpenAI API access can implement this approach to create their own AI-assisted moderation system. — Read More

Instead, we should empower workers and create mechanisms for redistribution.

I’ve been to a number of meetings and panels recently where intellectuals from academia, industry, media, and think tanks gather to discuss technology policy and the economics of AI. Chatham House Rules prevent me from saying who said what (and even without those rules, I don’t like to name names), but one perspective I’ve encountered increasingly often is the idea that we should try to “shape” or “steer” the direction of AI innovation in order to make sure it augments workers instead of replacing them. And the economist Daron Acemoglu has been going around advocating very similar things recently:

According to Acemoglu and [his coauthor] Johnson, the absence of new tasks created by technologies designed solely to automate human work will…simply dislocate the human workforce and redirect value from labour to capital. On the other hand, technologies that not only enhance efficiency but also generate new tasks for human workers have a dual advantage of increasing marginal productivity and yielding more positive effects on society as a whole… — Read More