Context and motivation: The development and operation of critical software that contains machine learning (ML) models requires diligence and established processes. Especially the training data used during the development of ML models have major influences on the later behaviour of the system. Runtime monitors are used to provide guarantees for that behaviour. Question / problem: We see major uncertainty in how to specify training data and runtime monitoring for critical ML models and by this specifying the final functionality of the system. In this interview-based study we investigate the underlying challenges for these difficulties. Principal ideas/results: Based on ten interviews with practitioners who develop ML models for critical applications in the automotive and telecommunication sector, we identified 17 underlying challenges in 6 challenge groups that relate to the challenge of specifying training data and runtime monitoring. Contribution: The article provides a list of the identified underlying challenges related to the difficulties practitioners experience when specifying training data and runtime monitoring for ML models. Furthermore, interconnection between the challenges were found and based on these connections recommendation proposed to overcome the root causes for the challenges.

While Artificial Intelligence (AI) technologies are progressing fast, compliance costs have become a huge financial burden for AI startups, which are already constrained on research & development budgets. This situation creates a compliance trap, as many AI startups are not financially prepared to cope with a broad spectrum of regulatory requirements. Particularly, the complex and varying regulatory processes across the globe subtly give advantages to well-established and resourceful technology firms over resource-constrained AI startups [1]. The continuation of this trend may phase out the majority of AI startups and lead to giant technology firms' monopolies of AI technologies. To demonstrate the reality of the compliance trap, from a field deployment perspective, we delve into the details of compliance costs of AI commercial operations.

Not all contracts are good, but all good contracts can be expressed as a finite-state transition system ("State-Transition Contracts"). Contracts that can be represented as State-Transition Contracts discretize fat-tailed risk to foreseeable, managed risk, define the boundary of relevant events governed by the relationship, and eliminate the potential of inconsistent contractual provisions. Additionally, State-Transition Contracts reap the substantial benefit of being able to be analyzed under the rules governing the science of the theory of computation. Simple State-Transition Contracts can be represented as discrete finite automata; more complicated State-Transition Contracts, such as those that have downstream effects on other agreements or complicated pathways of performance, benefit from representation as weighted finite-state transducers, with weights assigned as costs, penalties, or probabilities of transitions. This research paper (the "Research" or "Paper") presents a complex legal transaction represented as weighted finite-state transducers. Furthermore, we show that the mathematics/algorithms permitted by the algebraic structure of weighted finite-state transducers provides actionable, legal insight into the transaction.

We saw at least four videos in which Bakar and Yehia either appeared, or could be heard, extorting and abusing LGBTQ people before they uploaded the videos to Whatsapp, Youtube and Facebook. In one of these videos, an 18-year-old gay man we are calling Saeed is forced to, falsely, say he is a sex worker. I met him to hear about what happened next. He told me that he considered legal action but says his lawyer advised against this, telling him his sexuality would be perceived as more of a crime than the attack he suffered.

An expert said ChatGPT will do to search engine what Google did to Yellow Pages. The capabilities of ChatGPT, an artificial intelligence (AI) tool, is causing alarm among experts. In fact, Gmail developer Paul Buccheit said on Twitter that the tool could bring down search engine giant Google in "a year or two". The tool was launched in November 2022, and within a week, amassed more than one million users, according to a tweet from OpenAI employee Sam Altman. In the past few weeks, ChatGPT has demonstrated what it is capable of - by writing instant and complex essays, drafting marketing pitches, producing poems and jokes, and even drafting the speech of a Congressman in the US.

AI is rapidly changing the way Hollywood functions. It revolutionizes how stories are told, how movies are made, how audiences engage with content, and more. AI has the potential to disrupt the entire movie industry, from the way producers develop scripts to the way audiences consume content. AI is already being used to help filmmakers create more engaging stories. AI-powered screenwriting tools are being used to help writers generate ideas and structure their stories.

Who hasn't heard of ChatGPT which has taken the world by storm? From writing articles to acing exams to solving complicated arithmetic problems, the uncanny new artificial intelligence (AI) enabled chatbot has been spoken about on every platform. For the uninitiated, ChatGPT is a powerful new AI chatbot from OpenAI that generates text using Natural Language Processing (NLP). Here's what ChatGPT said about its expectations for Budget 2023: Increase in healthcare spending: The Indian government is expected to increase its spending on healthcare to combat the COVID-19 pandemic and to improve the overall health infrastructure in the country. Boosting the manufacturing sector: The government is expected to announce measures to boost the manufacturing sector, which has been hit hard by the pandemic, by providing financial incentives to manufacturers and increasing exports.

The artificial intelligence (AI) market has been on a swift growth path for several years – so much so that the industry is expected to reach $42.4 billion in 2023. This momentum will continue, and we're starting to realize it with the debut of powerful new AI-powered tools and services across industries. There has been a shift from the well-understood role of AI in analysis and prediction – helping data scientists and enterprises make sense of the world and chart their courses accordingly – to new and innovative systems, like DALL-E, that are producing entirely new artifacts that have never been seen before. But what's driving this exponential growth, and how will it affect the space in the coming year? AI is becoming a fundamental differentiator for business.

Working in the UX industry means living in a constant state of flux. Every day seems to bring new technologies, skills, business challenges, and user expectations to absorb. That's why every December, I eagerly await the release of UX Collective's State of UX report, in which authors Fabricio Teixeira and Caio Braga (plus collaborators) synthesize thousands of articles in order to put the past year into perspective and highlight emerging themes for the road ahead. The underlying theme for this year's report was anxiety. Massive layoffs at tech stalwarts like Facebook, Google, and Amazon, along with headlines about an economic slowdown, have some designers thinking about how to recession-proof their jobs. With headcounts shrinking, design teams are expected to do more with less, and former managers are returning to hands-on work.

DoNotPay has cancelled plans to have its AI-powered "robot lawyer" represent a defendant in a U.S. court after several human lawyer organizations objected to the experiment, according to company founder and CEO Joshua Browder. Browder hoped to make history by becoming the first lawyer to use artificial intelligence (AI) to argue a case in a court of law. As MetaNews previously reported, the plan was to use the company's AI chatbot in a traffic case scheduled for Feb. 22. "After receiving threats from State Bar prosecutors, it seems likely they will put me in jail for 6 months if I follow through with bringing a robot lawyer into a physical courtroom," he tweeted on Jan. 25. "DoNotPay is postponing our court case and sticking to consumer rights." Bad news: after receiving threats from State Bar prosecutors, it seems likely they will put me in jail for 6 months if I follow through with bringing a robot lawyer into a physical courtroom.