As ubiquitous as machine learning is in the enterprise, Levi's might not be the first brand that comes to mind when you think of AI smarts. As a company that has been producing jeans and other denim apparel since 1853, Levi Strauss & Co. seemed to be doing just fine without the intervention of neural networks and machine learning algorithms. But like so many large companies, Levi's has found plenty of uses for AI technology, from automating mundane tasks and analyzing denim-related data sets to helping its designers create new denim jacket designs. In 2019, Levi's formalized its years-long flirtation with AI by hiring Katia Walsh as the company's chief AI and strategy officer to lead its new global AI team. As part of her effort to integrate this bleeding edge tech into an established legacy brand, Walsh launched the company's first-ever Machine Learning Bootcamp in early 2021.

Welcome to our February 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we cover our latest New voices in AI interview, hear from a NeurIPS award winner, and get stuck into AAAI 2022. You may have seen the launch of our new series last month. In the latest episode, Isabel Cachola talks about how she got into AI and her work on interpretability of NLP models. In this interview, Bernard Koch tells us about research that won him, and co-authors Emily Denton, Alex Hanna and Jacob Foster, a best paper prize at NeurIPS 2021.

DURHAM, NC -- Whether preventing explosions on electrical grids, spotting patterns among past crimes, or optimizing resources in the care of critically ill patients, Duke University computer scientist Cynthia Rudin wants artificial intelligence (AI) to show its work. Especially when it's making decisions that deeply affect people's lives. While many scholars in the developing field of machine learning were focused on improving algorithms, Rudin instead wanted to use AI's power to help society. She chose to pursue opportunities to apply machine learning techniques to important societal problems, and in the process, realized that AI's potential is best unlocked when humans can peer inside and understand what it is doing. Now, after 15 years of advocating for and developing "interpretable" machine learning algorithms that allow humans to see inside AI, Rudin's contributions to the field have earned her the $1 million Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI).

As a key contribution, we adapt tools from the scenario approach to compute probably approximately correct (PAC) bounds on these transition probabilities, based on a finite number of samples of the noise. We capture these bounds in the transition probability intervals of a so-called interval Markov decision process (iMDP). This iMDP is robust against uncertainty in the transition probabilities, and the tightness of the probability intervals can be controlled through the number of samples. We use state-of-the-art verification techniques to provide guarantees on the iMDP, and compute a controller for which these guarantees carry over to the autonomous system. Realistic benchmarks show the practical applicability of our method, even when the iMDP has millions of states or transitions.

Urs Gasser (ugasser@cyber.harvard.edu) is the Dean of the new TUM School of Social Sciences and Technology at the Technical University of Munich, Germany, and a Faculty Director of the Berkman Klein Center for Internet & Society at Harvard University, Cambridge, MA, USA. Virgílio Almeida (virgilio@dcc.ufmg.br) is a Professor Emeritus of Computer Science at the Federal University of Minas Gerais (UFMG), Brazil, and a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University, Cambridge, MA, USA.

In his 1950's work Computing Machinery and Intelligence, Alan Turing (1912–1954), who is considered by many the father of Artificial Intelligence, laid out the following question: This question, despite its short length and old origin, still remains a frequent source of discussion, navigating the frontier between technology, philosophy, neuroscience and theology. However, more than half a century ago Turing proposed an indirect way to answer it: Through the famous Turing Test. Turing believed that for us to answer this question without ambiguity, the question itself must be rephrased, specifying or replacing the meaning of'think' and'machines'. Lets first see how we can smooth the'think' out of the equation. Turing proposed to do this by first modifying the question from "Can Machines Think?" to: "Can a machine do what we as thinking entities can do?"

The'Outnumbered' panel reacts to cyberattacks targeting Ukrainian websites as the U.S. warns of an imminent Russian attack. Rep. Ronny Jackson, R-Texas, is standing by his calls for President Biden, 79, to take a cognitive test, saying that Biden is "not fit to be our president right now" amid the Russia-Ukraine crisis. "The whole country is seeing his mental cognitive issues on display for over a year now, and there's really no question in most people's minds that there's something going on with him, that he's not cognitively the same as he used to be and, in my mind, not fit to be our president right now," Jackson told Fox News Digital in a phone interview. REPUBLICANS URGE BIDEN TO TAKE COGNITIVE TEST, SAY HIS'MENTAL DECLINE' HAS'BECOME MORE APPARENT' Ronny Jackson, the former White House physician who was elected on Nov. 3, 2020, to be the next congressman from Texas' 13th Congressional District. "Every time he gets up and talks to the American people, it's not just the American people that are watching him speak, it's the whole world, and that's part of what the problem is here," Jackson also said.

Akemi Leung knew her grandfather had been incarcerated at Heart Mountain in Wyoming during World War II. But he never spoke much about it. Only when she read and watched a video of his testimony at a congressional commission hearing did she learn more about what he suffered as one of more than 120,000 Americans of Japanese ancestry forced to leave their homes and live in concentration camps. "I just knew him to be a quiet person who liked to observe more than talk," Leung said. "Seeing the testimony helped illustrate how he was a leader."

What are the perilous spiritual implications of artificial intelligence, bioengineering, facial recognition, and other hi-tech applications we're accepting into our daily world with little concern? What does the Bible say about it all? Bible Gateway interviewed John C. Lennox (@ProfJohnLennox) about his book, 2084: Artificial Intelligence and the Future of Humanity (Zondervan, 2020). What is the title of this book intended to elicit in readers? Dr. John C. Lennox: It's intended to recall 1984, the dystopian novel by George Orwell who gave to the English language the idea of Big Brother.

Bernard Koch, Emily Denton, Alex Hanna and Jacob Foster won a best paper award, for Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research, in the datasets and benchmarks track at NeurIPS 2021. Here, Bernard tells us about the advantages and disadvantages of benchmarking, the findings of their paper, and plans for future work. Machine learning is a rather unusual science, partly because it straddles the space between science and engineering. The main way that progress is evaluated is through state-of-the-art benchmarking. The scientific community agrees on a shared problem, they pick a dataset which they think is representative of the data that you might see when you try to solve that problem in the real world, then they compare their algorithms on a score for that dataset.