Notwithstanding the question of bias, AI can have a positive social impact - for example, by automating large amounts of processes that currently depend on human labor but exact a steep cost on the individuals performing that labor. One such instance is identifying and stopping the spread of child abuse images on the dark web. Another example of AI's ability to relieve pressure on human agents and produce better outcomes us provided by Annie MOORE, developed by researchers at the Universities of Oxford and Lund. The software matches refugees to locations based on their needs and skills and the availability of resources and opportunities, and is increasing the likelihood of someone finding employment within three months by more than 20 per cent as well as improving their chances of integrating into their new communities. This data processing power is also, through machine learning, accelerating the development of new models for understanding how the world is changing - ClimateAI, for instance, has developed a forecasting engine for the agriculture and energy sectors that can model the impact of climate change on asset values over time periods ranging from a single season to an entire decade.

Businesses are witnessing a tipping point that can dramatically change the trajectory of their growth. Shifting attention from Big Data collection to real-time data consumption is setting the stage for a level of intelligence that requires a new way of thinking about processes and the applications that enable them. Fortunately, technologies such as artificial intelligence, machine learning, and blockchain are helping companies find a path forward. For many organizations, pulling together large volumes of data – which comprise diverse formats and originate from numerous sources – is creating a wave of pressure-tested innovations, data security and privacy, and a seismic shift in business value. And this outcome is changing not only the definition of industry leadership but also people's lives for the better.

CSR is gaining more and more importance in the business world. The companies with a good CSR strategy in place have a distinct competitive advantage. Consumers prefer products and services by socially responsible organisations even at a higher price. The companies have started to have CSR budgets to leverage this trend. However, many times the impact created by CSR programs does not reach its potential because of various glitches.

The media plays a central role in monitoring powerful institutions and identifying any activities harmful to the public interest. In the investing sphere constituted of 46,583 officially listed domestic firms on the stock exchanges worldwide, there is a growing interest `to do the right thing', i.e., to put pressure on companies to improve their environmental, social and government (ESG) practices. However, how to overcome the sparsity of ESG data from non-reporting firms, and how to identify the relevant information in the annual reports of this large universe? Here, we construct a vast heterogeneous information network that covers the necessary information surrounding each firm, which is assembled using seven professionally curated datasets and two open datasets, resulting in about 50 million nodes and 400 million edges in total. Exploiting this heterogeneous information network, we propose a model that can learn from past adverse media coverage patterns and predict the occurrence of future adverse media coverage events on the whole universe of firms. Our approach is tested using the adverse media coverage data of more than 35,000 firms worldwide from January 2012 to May 2018. Comparing with state-of-the-art methods with and without the network, we show that the predictive accuracy is substantially improved when using the heterogeneous information network. This work suggests new ways to consolidate the diffuse information contained in big data in order to monitor dominant institutions on a global scale for more socially responsible investment, better risk management, and the surveillance of powerful institutions.

Corporate citizenship has long been a community-stabilizing power. For decades, businesses have steadied struggling neighborhoods and schools, stocked shelves in food banks, funded shelters, rectified social inequalities, protected the environment and animals, and sought cures for what ails mankind. Today, corporate social responsibility (CSR) is aiming to provide more social good on a much larger scale--and big data and related technologies are the technical means they are using to reach that goal. "Digital-age technologies like blockchain, IoT, AI, and big data analytics are aiding corporate social responsibility practitioners to develop a sustainable and resilient world," says Kevin S. Parikh, author of "Digital Singularity: A Case for Humanity" and CEO of Avasant, a global management consulting firm. "Large-scale data collection combined with machine learning offers a new set of tools that opens up new avenues of research and greatly enhances the efficiency and efficacy of CSR work," Parikh adds.

When a man overseeing $5.7 trillion speaks, the global business community tends to listen. So when BlackRock founder Larry Fink, head of the world's largest asset management company, posted a letter to CEOs demanding greater attention to social impact, it sent shockwaves through corporations around the globe. In the letter, titled "A Sense of Purpose," Fink wrote, We … see many governments failing to prepare for the future, on issues ranging from retirement and infrastructure to automation and worker retraining. As a result, society increasingly is turning to the private sector and asking that companies respond to broader societal challenges. Fink's letter dropped just days before the 2018 World Economic Forum, an annual gathering of the global financial elite in Davos, Switzerland.

When you think of artificial intelligence (AI), what do you envision? Depending on what generation you were born into, you might think of HAL 9000's glowing red eye from 2001: A Space Odyssey, or you might think of the surprisingly humanlike Ava from Ex Machina. Or, if you're knee-deep in AI programming, you might envision AI as nothing more than a complex web of computational frameworks. For decades, pop culture and science fiction have illustrated the possibilities of AI--but these depictions aren't always accurate, and they aren't always in ways that positively encourage its development. By that same token, these depictions have inspired thousands, if not millions of curious minds to push the boundaries of what AI can accomplish (and even take efforts to improve our safety).

Robotics is an interdisciplinary branch of engineering and science that includes, inter alia, mechanical engineering, electrical engineering, and computer science. This emerging field of technological advancement deals with the connection of perception to action and where that connection is to be "intelligent," then artificial intelligence (AI) plays a fundamental role in robotics.

All tools can be used for good or ill. Even a broom can be used to sweep the floor or hit someone over the head. The more powerful the tool, the greater the benefit or damage it can cause. The last few months have brought this into stark relief when it comes to computer-assisted facial recognition – the ability of a computer to recognize people's faces from a photo or through a camera. This technology can catalog your photos, help reunite families or potentially be misused and abused by private companies and public authorities alike. Facial recognition technology raises issues that go to the heart of fundamental human rights protections like privacy and freedom of expression. These issues heighten responsibility for tech companies that create these products.

Kriti Sharma, vice president of AI and Ethics at Sage, shares what she wishes she knew as a teenager growing up in India and how tech can help underserved communities. You just built your first computer from scratch after reading a few books about them. But first, you need to endure a few more years of high school in India. I know you don't like school. But, I'm asking you to embrace your love for learning.