The operating room has long been defined by its hush-hush nature because surgeons are notoriously bad at acknowledging their own mistakes. These mistakes kill some 22,000 Americans each year. Many of the errors happen on the operating table, from leaving surgical sponges inside patients' bodies to performing the wrong procedure altogether. Now, Teodor Grantcharov, a surgeon and professor of surgery at Stanford, believes he's created the technology to create and analyze recordings of operations to help improve safety and surgical efficiency. It's the operating room equivalent of an airplane's black box: recording everything in the operating room via panoramic cameras, microphones, and anesthesia monitors before using artificial intelligence to help surgeons make sense of the data.

CERN, Europe's particle-physics laboratory, produces vast amounts of data, which are stored at its computer centre (pictured) and analysed with the help of artifical intelligence (AI). UK funders want to know whether AI could also assist in peer reviewing thousands of research outputs for nationwide quality audits.Credit: Dean Mouhtaropoulos/Getty Efforts to ease the workloads of peer reviewers by using artificial intelligence (AI) are gathering pace -- with one country's main research-evaluation exercise actively looking into ways of harnessing the technology. A study commissioned by the United Kingdom's main public research-funding bodies is examining how algorithms can assist in conducting peer review on journal articles submitted to the UK's Research Excellence Framework (REF). The REF, a national quality audit that measures the impact of research carried out at UK higher-education institutions, is a huge undertaking. In the latest iteration, the results of which were published in May 2022, more than 185,000 research outputs were evaluated from more than 76,000 academics based at 157 UK institutions.

Within the last decade, there has been growing awareness that causal inference can improve scientific research in many disciplines as interpretability and robustness become increasingly important (Doshi-Velez and Kim, 2017; Roscher et al., 2020; Marcinkevičs and Vogt, 2020; Moraffah et al., 2020). Causality is a crucial factor for gaining insights into the decision process of algorithms, which has many use cases such as avoiding bias and discrimination (Mehrabi et al., 2019), improving user experience (Zhou and Fu, 2007) and gathering biological insights (Angermueller et al., 2016). If the causal relation between variables is known, causality can be used to study the interaction between statistical units such as estimating the average effect of treatments (Imbens and Rubin, 2015; Holland, 1986), analyze their mediation (Berzuini et al., 2012), detect the root causes of anomalies (Janzing et al., 2019) or quantifying the causal influence of variables in a system (Janzing et al., 2013, 2020).

As it is, the world is unfair. The question now is, do we want automated tech to be unfair too? As we build more and more AI-dependent smart digital infrastructure in our cities and beyond, we have pretty much overlooked the emerging character of artificial intelligence that would have a profound bearing on our nature and future. Are we happy with algorithms making decisions for us? Naturally, one would expect the algorithm to possess discretion.

Facial-recognition software is increasingly being used to track individuals without their permission.Credit: David McNew/AFP/Getty China wants to be the world's leader in artificial intelligence (AI) by 2030. The United States has a strategic plan to retain the top spot, and, by some measures, already leads in influential papers, hardware and AI talent. Other wealthy nations are also jockeying for a place in the world AI league. A kind of AI arms race is under way, and governments and corporations are pouring eye-watering sums into research and development. The prize, and it's a big one, is that AI is forecast to add around US$15 trillion to the world economy by 2030 -- more than four times the 2017 gross domestic product of Germany.

Hotel bars are great places for people watching, seldom places for engaging conversation. I recently found myself sitting atop a tall stool in a city far from home, deep in conversation with a woman, like me, traveling for work. She, a hospitality professional in town to train a new cohort of hotel associates; me, in town for a tech conference. So, naturally, our conversation landed on the intersection of our specialities--the increasing use of technology in the hospitality industry. "I don't think the hospitality industry will become overtaken by technology--people want a human touch when they're traveling," I said confidently, and perhaps naively, to my newfound friend. She explained that, while in some places that's true (the closer to the water the more personal the experience needs to be, I learned), hotels are becoming more heavily outfitted with tech.

Automatica 2018 is one of Europe's largest robotics and automation-related trade shows and a destination for global roboticists and business executives to view new products. It was held June 19-22 in Munich and had 890 exhibitors and 46,000 visitors (up 7% from the previous show). The International Symposium on Robotics (ISR) was held in conjunction with Automatica with a series of robotics-related keynotes, poster presentations, talks and workshops. The ISR also had an awards dinner in Munich on June 20th at the Hofbräuhaus, a touristy beer hall and garden with big steins of beer, plates full of Bavarian food and oompah bands on each floor. From left: Stefan Lampa, CEO, KUKA; Prof Dr Bruno Siciliano, Dir ICAROS and PRISMALab, U of Naples Federico II; Ken Fouhy, Moderator, Editor in Chief, Innovations & Trend Research, VDI News; Dr. Kiyonori Inaba, Exec Dir, Robot Business Division, FANUC; Markus Kueckelhaus, VP Innovations & Trend Research, DHL; and Per Vegard Nerseth, Group Senior VP, ABB.