Ten years ago, Human Rights Watch united with other civil society groups to co-found the Stop Killer Robots campaign in response to emerging military technologies in which machines would replace human control in the use of armed force. There is now widespread recognition that weapons systems that select and attack targets without meaningful human control represent a dangerous development in warfare, with equally disastrous implications for policing. At the United Nations in October, 70 countries, including the United States, acknowledged that autonomy in weapons systems raises "serious concerns from humanitarian, legal, security, technological and ethical perspectives." Delegating life-and-death decisions to machines crosses a moral line, as they would be incapable of appreciating the value of human life and respecting human dignity. Fully autonomous weapons would reduce humans to objects or data points to be processed, sorted and potentially targeted for lethal action.

Thanks to 1MM readers of this newsletter, I hope that you enjoy the latest AI news, and insights. A programmer is suing Microsoft, GitHub, and OpenAI over artificial intelligence technology that generates its own computer code. Their model uses a wide variety of data, according to Sam's Club officials. Here's why that might not be a good thing. NannyML 0.8.0 is on Product Hunt: Don't forget to support them here https://lnkd.in/dru-pyXV

Rising need for AI Ethics workers is leading to exceedingly overworked and woefully underappreciated ... [ ] considerations. If there is one thing that we can almost all entirely agree on, I dare say it might be the abundance of worker burnout. Nary a day goes by that there aren't some blazing headlines about this worker or that worker-related burnout happening here or there. Some attribute burnout to concerns over wanting to keep their job and make a living. Others suggest that the burnout mania got especially underway when remote working became acceptable, pushing workers to potentially work nonstop and not have the conventional leave the office at 6 o'clock basis for curtailing work for the day. A slew of reasons exists and are continually bandied around for worker burnout. Those that work in the realm of Artificial Intelligence (AI) are right there in the worker burnout zone too. Yes, with all that excitement and hoopla about the present and future prospects of AI, there are humans toiling away to craft and field the AI. Software developers that specialize in making AI applications are dearly sought by companies. Once onboard, the AI programmers are bound to discover that there is a lot of AI work going on. Indeed, the odds are that a veritable fifteen pounds of AI are needed and yet the AI teams are barely able to produce five pounds given the team size and AI complexities involved.

Nearly every new generation of technology -- even online search engines -- has faced similar legal challenges. In late June, Microsoft released a new kind of artificial intelligence technology that could generate its own computer code. Called Copilot, the tool was designed to speed the work of professional programmers. As they typed away on their laptops, it would suggest ready-made blocks of computer code they could instantly add to their own. Many programmers loved the new tool or were at least intrigued by it.

Parents and teachers across the world are rejoicing as students have returned to classrooms. But unbeknownst to them, an unexpected insidious academic threat is on the scene: a revolution in artificial intelligence has created powerful new automatic writing tools. These are machines optimised for cheating on school and university papers, a potential siren song for students that is difficult, if not outright impossible, to catch. Of course, cheats have always existed, and there is an eternal and familiar cat-and-mouse dynamic between students and teachers. But where once the cheat had to pay someone to write an essay for them, or download an essay from the web that was easily detectable by plagiarism software, new AI language-generation technologies make it easy to produce high-quality essays.

Ken Bromley Art Supplies has teamed up with Lacuna 5 to raise awareness of the climate crisis -- the greatest threat of our generation -- through the power of art. A series of AI-generated images envision how famous artists from history would depict some of the most pressing issues that threaten our environment, from deforestation to plastic pollution and factory farming. When coupled with the names of famous artists such as Van Gogh, Yayoi Kusama or Claude Monet, the AI technology has created completely unique pieces of activist art, including a portrait of Swedish teenage environmental activist Greta Thunberg in the signature pop art aesthetics of Andy Warhol. Earlier in November, political leaders from across the world convened at the COP26 summit to accelerate global action towards climate change prevention. Increasingly in recent times, there have also been several incidents involving climate activists destroying famous artworks to protest that'protecting life is more important than protecting art.'

Transformers are widely used in natural language processing, where they consistently achieve state-of-the-art performance. This is mainly due to their attention-based architecture, which allows them to model rich linguistic relations between (sub)words. However, transformers are difficult to interpret. Being able to provide reasoning for its decisions is an important property for a model in domains where human lives are affected. With transformers finding wide use in such fields, the need for interpretability techniques tailored to them arises. We propose a new technique that selects the most faithful attention-based interpretation among the several ones that can be obtained by combining different head, layer and matrix operations. In addition, two variations are introduced towards (i) reducing the computational complexity, thus being faster and friendlier to the environment, and (ii) enhancing the performance in multi-label data. We further propose a new faithfulness metric that is more suitable for transformer models and exhibits high correlation with the area under the precision-recall curve based on ground truth rationales. We validate the utility of our contributions with a series of quantitative and qualitative experiments on seven datasets.

Recent work has demonstrated that natural language processing techniques can support consumer protection by automatically detecting unfair clauses in the Terms of Service (ToS) Agreement. This work demonstrates that transformer-based ToS analysis systems are vulnerable to adversarial attacks. We conduct experiments attacking an unfair-clause detector with universal adversarial triggers. Experiments show that a minor perturbation of the text can considerably reduce the detection performance. Moreover, to measure the detectability of the triggers, we conduct a detailed human evaluation study by collecting both answer accuracy and response time from the participants. The results show that the naturalness of the triggers remains key to tricking readers.

Artificial Intelligence (AI) is much in the news these days. As a concept, AI seems completely unrelated to the field of law. Although, AI and Law are intricately intertwined and are becoming more so each day. In this lecture, Professor Harry Surden – a former software engineer and leader of the emerging interdisciplinary field of AI and Law – will explore: What is Artificial Intelligence? How is law affecting Artificial Intelligence?

Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses. This lawsuit is mainly because, as most of you may know, Copilot has been found to regurgitate long sections of licensed code without providing credit, which was discovered by many users.