Women's groups are calling for tech developers to take into account women's safety. Women's groups are calling for tech developers to take into account women's safety. Domestic abusers are increasingly using AI, smartwatches and other technology to attack and control their victims, a domestic abuse charity says. Record numbers of women who were abused and controlled through technology were referred to Refuge's specialist services during the last three months of 2025, including a 62% increase in the most complex cases to total 829 women. There was also a 24% increase in referrals of under-30s.

Can Bike Riders and Self-Driving Cars Be Friends? Some cycling advocates are on board with robotaxis. Others see the self-driving car boom as perpetuating auto dependency. Los Angeles is a car city, and it's rarely more obvious than from a vulnerable perch on top of a bicycle . Among big cities in the US, LA has a middling-to-bad reputation for bike riding.

While analysing challenges in pilot projects developing AI with marginalized communities, we found it difficult to express them within commonly used paradigms. We therefore constructed an alternative conceptual framework to ground AI development in the social fabric -- the Cloud Weaving Model -- inspired (amongst others) by indigenous knowledge, motifs from nature, and Eastern traditions. This paper introduces and elaborates on the fundamental elements of the model (clouds, spiders, threads, spiderwebs, and weather) and their interpretation in an AI context. The framework is then applied to comprehend patterns observed in co-creation pilots approaching marginalized communities, highlighting neglected yet relevant dimensions for responsible AI development.

In light of the April 2021 announcement of the world's first legislative framework for regulating Artificial Intelligence (AI), the European Artificial Intelligence Act (EU AIA), now is an opportune time for developers to revisit their strategies for testing AI applications. Incoming regulations mean that the group of stakeholders who care about your testing results just got bigger and more involved. The stakes are high, not least because companies that violate the terms of the legislation could face fines higher than those levied under the General Data Protection Act (GDPR). For the purpose of transparency, certain types of AI also have to make their accuracy metrics available to users, which adds to the pressure to get functional testing right. Following on from Applause's step-by-step guide to training and testing your AI algorithm, this article summarizes how developers should be testing AI applications in anticipation of the new era of AI regulations.

In 2019, UnitedHealthcare's health-services arm, Optum, rolled out a machine learning algorithm to 50 healthcare organizations. With the aid of the software, doctors and nurses were able to monitor patients with diabetes, heart disease and other chronic ailments, as well as help them manage their prescriptions and arrange doctor visits. Optum is now under investigation after research revealed that the algorithm (allegedly) recommends paying more attention to white patients than to sicker Black patients. Today's data and analytics leaders are charged with creating value with data. Given their skill set and purview, they are also in the organizationally unique position to be responsible for spearheading ethical data practices.

Voice technology in education is taking over the academic sphere for both developers and learners. Marissa, from Alexa Education sheds more light on how the phenomenon is revolutionizing experiences in the education sector. Marissa has gathered massive passion for voice technology in education during her early days when she was producing CD-ROM educational content for'edutainment'. Her interest grew as she migrated to Microsoft where she worked on several projects that impacted the education industry such as Xbox and Encarta. Now, during her tenure in Amazon's Alexa Education, Marissa explains how her team is developing a solid connection between institutions and their stakeholders by providing efficient ways in which learners access educational content powered by technology.

Tesla has reportedly acquired the four-year-old startup DeepScale, which provides interesting insight into the state of Artificial Intelligence in assisted and automated driving. Operating on $18M in venture funding, DeepScale described themselves as developers of perceptual systems for semi-autonomous and autonomous vehicles, focusing on low-wattage processors used in mass-market automotive crash avoidance systems to power more accurate perception. This is an important niche in the intelligent vehicle eco-system; the volumes of systems like automatic emergency braking (AEB) are increasing rapidly due to OEMs making them a standard feature. JATO reports that AEB sales as standard equipment have increased from 6% in Model Year 2016 to 39% in Model Year 2018, with the fitment rate rising to 49% of vehicles sold for Model Year 2019. As one who well remembers the refrain "safety doesn't sell" in automotive circles during the 1990's, this is remarkable and gladdening.

Many new computer devices do not understand Icelandic, a unique descendant of the Old Norse language filled with ultra-descriptive words such as Hundslappadrifa, or "heavy snowfall with large flakes occurring in calm wind." This omission is compounding a bigger issue on the North Atlantic island of about 340,000 people. SEE ALSO: Companies will have to prove equal pay in Iceland now, and it's pretty great Icelandic, seen by residents as a source of identity and pride, is losing ground as English becomes the lingua franca of mass tourism and voice-activated devices, the Associated Press reported. Linguistic experts have warned the language is at risk of dying out in the modern world, particularly as tourism booms and foreign workers find more jobs on the rugged island. Unless the government, educators, families, and tech developers make a concerted effort to preserve Icelandic, it could easily be relegated to history books.