new Meantime, the partnership with MITRE will bolster the vulnerability research, classification, and risk scoring that powers the AI Risk Database by more closely tying it to the MITRE ATLAS framework. The database is also set to be hosted under the broader set of open source MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) tools. MITRE is leading the charge in identifying threats and risks to AI with ATLAS, a framework and knowledge base that includes a list of adversary tactics and techniques based on real-world attack observations and AI red teaming. — darkreading.com, 17h ago

new CN.AI is focusing its AI Human business on the B2B market for organizations and has recently entered the B2C market by developing and launching KT AI Human Studio. In this regard, the official said, “We have expanded our horizons to the B2C market because we believe that there will come a time when not only companies but also individuals, such as so-called ‘persons with two jobs,’ freelancers, and lecturers, will freely use the AI Human. Based on our generative AI technology and our belief that ‘AI creates opportunities for everyone,’ we will continue to research and develop technologies to lead the ‘With AI’ era where everyone can easily and quickly use AI.”... — Journal of Cyber Policy, 19h ago

new For all of the bravado of AI, before we become too dazzled or dismayed (depending on which side of this issue you reside), at AI’s potential impact on projects, it is worthwhile to sit back with a skeptical bird’s eye view. After all, as we humans evolved throughout the information age of the mid to late twentieth century, AI can just be considered the latest development in a long series of technological advances driven by the engine of human information input. Even if every one of the improvements stated above are tangible, how well does it translate to the ultimate outcome? Organizations around the globe have been trying to digitalize and computerize, some as early as the 1960s and 1970s. Digitization and computerization promised a revolution in productivity through automation, streamlining, and making humans redundant. But the road to a more significant productivity boost has been arduous at best. One of the primary reasons is captured in the Theory of Constraints (TOC) developed by Eliyahu M. Goldratt, an Israeli physicist turned business management guru. In his landmark book The Goal, which sold over 6 million copies, he explains the importance of focusing on the right constraints to improve the overall system. For projects, the constraints are generally not within the technology and tools, but within humans. — Healthcare Business Today, 1d ago

new Policymakers are increasingly considering risk-based assessments of AI systems, such as the EU AI Act. We believe that in this context, AI systems with the potential for deception should be classified at least as “high-risk.” This classification would naturally lead to a set of regulatory requirements, including risk assessment and mitigation, comprehensive documentation, and record-keeping of harmful incidents. Second, we suggest passing ‘bot-or-not’ laws similar to the one in California. These laws require AI-generated content to be accompanied by a clear notice informing users that the content was generated by an AI. This would give people context about the content they are viewing and mitigate the risk of AI deception. — Montreal AI Ethics Institute, 1d ago

new Exploring the creative capability of artificial intelligence, a study recently published in Scientific Reports illuminates the captivating interplay between human ingenuity and computational creativity. Researchers Mika Koivisto and Simone Grassini utilized the Alternate Uses Task (AUT) as a medium to explore divergent thinking, a cognitive process wherein individuals formulate varied ideas or solutions in response to a singular task. Encompassing responses from 256 human participants and three advanced AI chatbots—ChatGPT3, ChatGPT4, and Copy.Ai—the study scrutinized creative alternatives for commonplace objects such as a pencil and a candle. Delving into semantic distance and creativity as measured through computational and human evaluators, respectively, the findings unveiled a nuanced narrative: while chatbots, on average, surpassed human scores in semantic distance and creativity, the peak of human creativity ultimately eclipsed the AI-generated responses in seven of the eight scoring categories. Thus, while AI chatbots demonstrably weave a tapestry of ideas that align with, or even surpass, average human creativity, the best level of human imaginative thought, at least presently, remains unparalleled. This investigative foray invites further exploration into the application and integration of AI within the realm of creative processes, foreshadowing an intriguing symbiosis of human and artificial creative potentials. — Montreal AI Ethics Institute, 1d ago

new LLMs have been all over the news for the past year – both in terms of their ability to tell knock-knock jokes and answer questions, but also because of their visible mistakes – like that AI-generated recipe for chlorine gas and made up legal cases that got a lawyer fined. They are presented as ‘general purpose technologies’ [1] with ‘emergent properties’ [2] – but what are they, and how much of this is true?... — Montreal AI Ethics Institute, 1d ago

new The chatbot's ability to accurately interpret and contextually apply scientific information represents a significant advancement in AI technology. By integrating a curated set of scientific publications, Yager's AI model ensures that the chatbot's responses are not only relevant but also deeply rooted in the actual scientific discourse. This level of precision and reliability is what sets it apart from other general-purpose AI tools, making it a valuable asset in the scientific community for research and development. — unite.ai, 1d ago

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new The job of marketing professionals, however consistent in goal, allows for a nearly infinite amount of variety. With that comes freedom to be creative, inventive, and forward thinking. While such systems as AI and big data analysis have enabled impressive and effective ways to measure effective marketing strategies, there are still other ways to go about enhancing marketing campaigns for successful returns.With the number of analytical tools, proven marketing strategies, predictive consumer behavioral patterns, and design techniques, there are still a number of other ways to engage consumers.Here are some design thinking tools and techniques which can help to create compelling digital marketing content. However, let’s begin by unpacking what is meant by design thinking. — SmartData Collective, 1d ago

new Structured guidance for all AI tool developers and users: This type of AI policy can act as a user manual for both AI developers and users of these tools, as it considers the entire AI lifecycle, from development to deployment to ongoing monitoring and fine-tuning. The standardized rules that are part of this type of policy facilitate cross-organizational buy-in and help your technical teams create a roadmap for AI best practices in real-world scenarios. — eWEEK, 1d ago

new Through rigorous validation, we confirm LLMCarbon’s accuracy in estimating both the operational and embodied carbon footprints of LLMs. In operational phases, our tool demonstrated disparities of 8.2% or less when compared to actual data, surpassing existing tools in precision. Moreover, LLMCarbon’s estimations of embodied carbon footprints closely align with publicly available data, showcasing an error margin of less than 3.6%. These findings highlight LLMCarbon’s invaluable role in guiding the development and usage of LLMs towards a more sustainable and environmentally conscious AI future. — Montreal AI Ethics Institute, 1d ago

new Artificial intelligence (AI) is at the forefront of boosting efficiency. AI systems can analyze large datasets, automate routine tasks, and even make predictive analyses, saving time and reducing the potential for human error. — Techiexpert.com, 2d ago

new We can run large numbers of experiments to find the most effective interventions, and we can also run it in a variety of simulated environments and test whether it behaves as expected both with and without the cognitive intervention. Each time the AI’s “memories” can be reset, making the experiments perfectly reproducible and preventing the AI from adapting to our actions, very much unlike experiments in psychology and social science. — alignmentforum.org, 2d ago

new Spray adds agencies that want to innovate with AI must also be willing to accept risk and failure, and be diligent when it comes to compliance. “The reality is that adopting new technology is not going to be a smooth road,” she says. “We have to consider things from lots of different perspectives, from legal to regulatory to ethics. How do you create those governance processes – do you have them already or do you need to do that now?”... — Cision, 2d ago

new ...“Meanwhile most POCs dazzled by the mirage of democratized, outsourced GenAI crash headfirst into the realities of operationalizing production-grade GenAI applications, leading to widespread disillusionment,” Carlsson continued. “It turns out that human intelligence about AI is the most important factor for GenAI success, and ‘Generalized Pre-trained Transformer Models’ are more valuable when they are specialized for specific use cases and verticals.”... — Datanami, 2d ago