Fox News anchor Julie Banderas reacts to the vice president's gaffe and CNN calling Dylan Mulvaney a man on'Jesse Watters Primetime.' After a meeting with executives from key AI technology firms, including Amazon, Google, Meta, Microsoft, and OpenAI, President Biden announced that the companies had agreed to four commitments. These range from best practices, such as enhancing system security and product testing, to the'moonshot' goals of watermarking AI content and using AI to solve critical societal challenges in areas like health care. While solving societal challenges is aspirational, watermarking AI-produced content may be challenging. It also raises questions regarding what constitutes'AI generated' and whether the government should push technology providers to label content produced using their tools.

Sweden's attitude towards innovation is perhaps best exemplified by the Swedish innovation agency, Vinnova, a government agency founded in 2001 based on a series of predecessors going back to at least 1968. The innovation agency functions much like its counterparts in other countries, similarly to the Finnish Funding Agency for Technology and Innovation (Tekes) in neighbouring Finland, and to the part of the US National Science Foundation (NSF) that does seed funding on the other side of the Atlantic. The Swedish government gives Vinnova more than €300m each year to invest through grants to different kinds of actors, which might be small companies, research institutes, large competence centres, or consortia of companies working together on projects. Vinnova invests this money along 10 different themes, including sustainable industry and digital transformation. To report on the social and economic effects of its funding, the agency produces two impact studies annually.

Being the Silicon Valley hi-tech giant, Google has started implementing cutting-edge technologies like artificial intelligence to provide efficiency to the world. Google AI conducts research to advance the state-of-the-art through AI-based software. AI at Google develops artificial intelligence tools to ensure that the world can access the strong and smart functionalities of AI. The mission of Google AI is to organize the real-time information and make it accessible to the world for multiple different useful purposes for each and every sector. The implementation of artificial intelligence has offered Google Translate, Google Assistant, and many more with new ways of solving real-life complicated problems.

In the digital world, top AI companies in social good are coming up with innovative AI solutions to address worldly challenges. Artificial intelligence for social good is making significant impacts in diverse industries.

Motivational digital systems offer capabilities to engage and motivate end-users to foster behavioral changes towards a common goal. In general these systems use gamification principles in non-games contexts. Over the years, gamification has gained consensus among researchers and practitioners as a tool to motivate people to perform activities with the ultimate goal of promoting behavioural change, or engaging the users to perform activities that can offer relevant benefits but which can be seen as unrewarding and even tedious. There exists a plethora of heterogeneous application scenarios towards reaching the common good that can benefit from gamification. However, an open problem is how to effectively combine multiple motivational campaigns to maximise the degree of participation without exposing the system to counterproductive behaviours. We conceive motivational digital systems as multi-agent systems: self-adaptation is a feature of the overall system, while individual agents may self-adapt in order to leverage other agents' resources, functionalities and capabilities to perform tasks more efficiently and effectively. Consequently, multiple campaigns can be run and adapted to reach common good. At the same time, agents are grouped into micro-communities in which agents contribute with their own social capital and leverage others' capabilities to balance their weaknesses. In this paper we propose our vision on how the principles at the base of the autonomous and multi-agent systems can be exploited to design multi-challenge motivational systems to engage smart communities towards common goals. We present an initial version of a general framework based on the MAPE-K loop and a set of research challenges that characterise our research roadmap for the implementation of our vision.

Over the last couple of years, Artificial Intelligence (AI) has changed from a technology with potential to an instrument of national importance across the world. The first demonstration of applications of AI has happened in the consumer space, and significant economic value has been created, mainly through targeted advertising by internet giants in the US and China. According to a report by PwC, AI could contribute a whopping $15.7 trillion to global GDP by 20301. However, for India, AI is much more than just a piece of this pie. For India, the real power of AI lies in its transformative potential to address massive societal challenges that were traditionally considered to be beyond the purview of computing.

The robots are taking over. It seems like a common refrain these days as more and more Artificial Intelligence (AI) and machine learning operations are incorporated into everyday work processes and activities. Many people fear the loss of their jobs to AI and the impact of new technologies on their future career growth. While there's no doubt that AI and machine learning are disrupting the way we live and work, the reality is that AI will create more jobs and opportunities than it destroys. From transforming businesses and boosting productivity to addressing "moonshot" societal challenges, there are many positive applications of AI.

This interdisciplinary event teamed data science, engineering, and policy students to explore solutions to real societal challenges submitted by sponsor organizations. The hackathon, subtitled "Data to Decisions," was organized and run by students from MIT's Institute for Data, Systems, and Society (IDSS). Participants used datasets provided by nonprofit, education, and government institutions to pitch solutions to complex challenges in cybersecurity, health, energy and climate, transportation, and the future of work. A panel of judges evaluated the pitches and read final policy proposals. "It's a different type of hackathon in that it is focused on public policy outcomes," says Amy Umaretiya, a student organizer with IDSS's Master's program in Technology and Policy (TPP).

This interdisciplinary event teamed data science, engineering, and policy students to explore solutions to real societal challenges submitted by sponsor organizations. The hackathon, subtitled "Data to Decisions," was organized and run by students from MIT's Institute for Data, Systems, and Society (IDSS). Participants used datasets provided by nonprofit, education, and government institutions to pitch solutions to complex challenges in cybersecurity, health, energy and climate, transportation, and the future of work. A panel of judges evaluated the pitches and read final policy proposals. "It's a different type of hackathon in that it is focused on public policy outcomes," says Amy Umaretiya, a student organizer with IDSS's Master's program in Technology and Policy (TPP).

In the famous sci-fi book (and movie), the "precrime" police is able to stop murders before they happen thanks to humans who predict the future. The concept is fascinating and is an interesting example of a possible use of Artificial intelligence. But we would leave the decision and control fully to the machines which we must not let happen in the real world. People have the right to own their future and no machine can be deciding on their behalf. When I read articles such as the recent one in La Stampa by Lorenzo Longhitano that a computer can predict what a chance of curing a sick person is and whether it is reasonable to admit her or him to the hospital, I think we need to draw a clear line.