With the ever-growing adoption of artificial intelligence (AI), AI-based software and its negative impact on the environment are no longer negligible, and studying and mitigating this impact has become a critical area of research. However, it is currently unclear which role environmental sustainability plays during AI adoption in industry and how AI regulations influence Green AI practices and decision-making in industry. We therefore aim to investigate the Green AI perception and management of industry practitioners. To this end, we conducted a total of 11 interviews with participants from 10 different organizations that adopted AI-based software. The interviews explored three main themes: AI adoption, current efforts in mitigating the negative environmental impact of AI, and the influence of the EU AI Act and the Corporate Sustainability Reporting Directive (CSRD). Our findings indicate that 9 of 11 participants prioritized business efficiency during AI adoption, with minimal consideration of environmental sustainability. Monitoring and mitigation of AI's environmental impact were very limited. Only one participant monitored negative environmental effects. Regarding applied mitigation practices, six participants reported no actions, with the others sporadically mentioning techniques like prompt engineering, relying on smaller models, or not overusing AI. Awareness and compliance with the EU AI Act are low, with only one participant reporting on its influence, while the CSRD drove sustainability reporting efforts primarily in larger companies. All in all, our findings reflect a lack of urgency and priority for sustainable AI among these companies. We suggest that current regulations are not very effective, which has implications for policymakers. Additionally, there is a need to raise industry awareness, but also to provide user-friendly techniques and tools for Green AI practices.

AI-based software systems are rapidly becoming essential in many organizations [1]. However, the focus on the technical side of building artificial intelligence (AI)-based systems are most common, and many projects, more often than not, fail to address critical human aspects during the development phases [2, 3]. These include but are not limited to age, gender, ethnicity, socio-economic status, education, language, culture, emotions, personality, and many others [4]. Ignoring human-centered aspects in AI-based software tends to produce biased and non-inclusive outcomes [5]. Shneiderman [6] emphasizes the dangers of autonomy-first design in AI and the hidden biases that follow. Misrepresenting human aspects in requirements for model selection and data used in training AI algorithms can lead to discriminatory decision procedures even if the underlying computational processes were unbiased [7]. For example, a study by Carnegie Mellon revealed that women were far less likely to receive high-paying job ads from Google than men [8] due to the under-representation of people of color and women in high paying IT jobs. Studies on human-centered design aim to develop systems that put human needs and values at the center of software development and clearly understand the context of the software system's usage [2, 9].

AI can improve or worsen job quality. What constitutes a quality job? If you were to ask family and friends, they would probably say good pay, benefits, and stable working conditions, but for many workers, workplace technologies, especially AI, are affecting job quality. That's important because the U.S. has a serious job quality problem. The number one ESG challenge companies are grappling with is the treatment of workers.

Shopping online has become more and more popular for consumers, especially during the pandemic. With online shopping, customers cannot only buy necessities but also enjoy shopping at home. And the quick shipping speed and free return policy also make the shopping experience more reasonable and enjoyable. To provide a better online shopping experience, AI plays an important role in improving online payments. In brief, the use of AI in online payments serves consumers who need to pay. The purpose of AI applications is to provide an easier, safer, and more enjoyable payment process, thus encouraging online shopping.

Doctors in China have been given a new powerful tool to help them quickly diagnose potential coronavirus sufferers. Called inferVISION, this AI-based software can quickly highlight potential problem cases in record time. A team of physicians in Wuhan, China, at the Zhongnan Hospital are using GPU-accelerated software to detect the visual signs of COVID-19. This AI-based software relies on NVIDIA GPUs for both training and inference and is alleviated the pressure on overworked staff to screen patients for the virus. The software is greatly helping medical staff to prioritize those who are likely to have contracted the virus. The software has been developed by a Beijing-based startup called inferVISION.

The term Artificial Intelligence (AI) has been popularised by companies such as Google and Amazon and often draws connotations of robots, natural language assistance or self-driving cars. Whilst all of these are popular examples of the more interesting use cases for AI, the oftentimes invisible technology is already starting to impact everyday life. In the industrial world, AI is a technology we're increasingly finding uses for and one that will be a big focus for companies in 2022. For industrial applications, AI combines data science with machine learning and domain expertise to perform a wide variety of critical functions that may range from monitoring essential infrastructure to ensuring that machinery continues to operate as optimally as possible. To fully realise the benefits of AI, industrial companies must work to understand which processes can benefit most from AI and focus on a highly specific set of potential operational efficiencies, quality gains and safety enhancements.

A brief list of our favorite sourcing and recruiting tools, including those that are based on self-learning algorithms. Along with other parts of the business, human resources have also been digitized since the pandemic started. It became obvious that you cannot organize a physical interview with the potential candidates. And that many of them left crowded, expensive cities and went home, to their native towns or countries. Traveling is now open again, but it does not give a guarantee that one can hire new developers or marketers in a traditional way, like it was before the COVID19.

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.

Picture this: As a Covid-19 patient fights for her life on a ventilator, software powered by artificial intelligence analyzes her vital signs and sends her care providers drug-dosing recommendations -- even as the same software simultaneously analyzes in real time the vital signs of thousands of other ventilated patients across the country to learn more about how the dosage affects their care and automatically implements improvements to its drug-dosing algorithm. This type of AI has never been allowed by the Food and Drug Administration. But that day is coming. AI that continuously learns from new data and modifies itself, called adaptive AI, faces some steep barriers. All FDA-cleared or approved AI-based software is "locked," meaning the manufacturer cannot allow adaptations for real-world use without new testing to confirm that it still works properly.

Deepfakes may have innocent and fun applications -- companies like RefaceAI and Morphin enable users to swap their faces with those of popular celebrities in a GIF or digital content format. But like a double-edged sword, the more realistic the content looks, the greater the potential for deception. Deepfakes have been ranked by experts as one of the most serious artificial intelligence (AI) crime threats based on the wide array of applications it can be used for criminal activities and terrorism. A study by University College London (UCL) identified 20 ways AI can be deployed for the greater evil and these emerging technologies were ranked in order of concern in accordance with the severity of the crime, the profit gained, and the difficulty in combating their threats. When the term was first coined, the idea of deepfakes triggered widespread concern mostly centered around the misuse of the technology in spreading misinformation, especially in politics.