There are many advantages of grasping how an AI-enabled system has arrived at a particular output. Explainability can help developers ensure that their algorithms are working as expected and meeting regulatory standards. It also makes it possible for those affected by an AI decision to challenge or change that outcome. But before we hold AI machines to such high levels of explainability, there is a crucial question: How good are humans in explaining themselves? Riding a bicycle is considered a very simple human action.

Local governments increasingly use artificial intelligence (AI) for automated decision-making. Contestability, making systems responsive to dispute, is a way to ensure they respect human rights to autonomy and dignity. We investigate the design of public urban AI systems for contestability through the example of camera cars: human-driven vehicles equipped with image sensors. Applying a provisional framework for contestable AI, we use speculative design to create a concept video of a contestable camera car. Using this concept video, we then conduct semi-structured interviews with 17 civil servants who work with AI employed by a large northwestern European city. The resulting data is analyzed using reflexive thematic analysis to identify the main challenges facing the implementation of contestability in public AI. We describe how civic participation faces issues of representation, public AI systems should integrate with existing democratic practices, and cities must expand capacities for responsible AI development and operation.

We consider the problem of learning the dynamics of a linear system when one has access to data generated by an auxiliary system that shares similar (but not identical) dynamics, in addition to data from the true system. We use a weighted least squares approach, and provide a finite sample error bound of the learned model as a function of the number of samples and various system parameters from the two systems as well as the weight assigned to the auxiliary data. We show that the auxiliary data can help to reduce the intrinsic system identification error due to noise, at the price of adding a portion of error that is due to the differences between the two system models. We further provide a data-dependent bound that is computable when some prior knowledge about the systems is available. This bound can also be used to determine the weight that should be assigned to the auxiliary data during the model training stage.

Art is subjective and everyone has their own opinion about it. When I saw the expressionist painting Blue Poles, by Jackson Pollock, I was reminded of the famous quote by Rudyard Kipling, "It's clever, but is it Art?" Pollock's piece looks like paint messily spilled onto a drop sheet protecting the floor. The debate of what constitutes art has a long history that will probably never be settled, there is no definitive definition of art. Similarly, there is no broadly accepted objective definition for the quality of a piece of art, with the closest definition being from Orson Welles, "I don't know anything about art but I know what I like." Similarly, people recognize unfair bias when they see it, but it is quite difficult to create a single objective definition.

Though others have interviewed ChatGPT, I had some anxiety-riddled questions of my own: Will you take my job? Is the singularity upon us? These questions are half facetious, half serious. If you've been hidden away and somehow missed the ruckus, here's what all the commotion's about: In November, conversational AI tool ChatGPT took the world by storm, crossing one million users a mere five days after its release, according to its developer, San Francisco's OpenAI. If you are still one of those who think this is all hype, take it up with Microsoft (MSFT).

Knowledge-enhanced neural machine reasoning has garnered significant attention as a cutting-edge yet challenging research area with numerous practical applications. Over the past few years, plenty of studies have leveraged various forms of external knowledge to augment the reasoning capabilities of deep models, tackling challenges such as effective knowledge integration, implicit knowledge mining, and problems of tractability and optimization. However, there is a dearth of a comprehensive technical review of the existing knowledge-enhanced reasoning techniques across the diverse range of application domains. This survey provides an in-depth examination of recent advancements in the field, introducing a novel taxonomy that categorizes existing knowledge-enhanced methods into two primary categories and four subcategories. We systematically discuss these methods and highlight their correlations, strengths, and limitations. Finally, we elucidate the current application domains and provide insight into promising prospects for future research.

One day in mid-November, workers at OpenAI got an unexpected assignment: Release a chatbot, fast. The chatbot, an executive announced, would be known as "Chat with GPT-3.5," and it would be made available free to the public. The announcement confused some OpenAI employees. All year, the San Francisco artificial intelligence company had been working toward the release of GPT-4, a new AI model that was stunningly good at writing essays, solving complex coding problems and more. After months of testing and fine-tuning, GPT-4 was nearly ready.

In comparison, according to Sensor Tower, TikTok took about nine months after its global launch to reach 100 million users, while Instagram took 2.5 years ChatGPT can create articles, essays, jokes, and even poems in response to prompts. OpenAI, a private company backed by Microsoft Corp, made it public for free in late November. It is worth noting that ChatGPT does not work in Ukraine OpenAI closed access to the API on which the new chatbot works for Ukrainians. The Ministry of Digitization appealed to the developer to open access to it for Ukrainians, and the Minister of Digital Transformation Mykhailo Fedorov tagged the OpenAI company on his Twitter. After all, all major issues in 2022 will be resolved there However, the issue of access to technology in Ukraine has not yet been resolved.

On January 7, the K-Start-ups attending the Consumer Entertainment Show, or CES in Las Vegas were awarded with the Global Media Awards 2023. They were selected in advance by press media from Europe, South Korea, Japan and the US as outstanding domestic innovators in attendance of the event. The awards were given based on the competitiveness, how likely they are to successfully enter the global market, how marketable they are and the investment value. The ceremony was held in the K-Startup Joint Pavilion. This year, the size of CES grew by an amazing 50% compared to 2022, with more than 2,800 companies attending from 173 countries around the world.

Moving your body while listening to sounds may help you more accurately perceive the passing of time during a particular event. Past research suggests that this finding could help to improve treatments for conditions such as Parkinson's disease, which often affects a person's motor function and the timing of their movements. Improved accuracy to our perception of time may help doctors to assess the effectiveness of interventions that aim to ease these symptoms. When an event occurs, the body has various means of measuring how long it lasted. For example, moving our body can help to improve our accuracy when counting the length of auditory tones.