Accenture's partnership with AI4ALL gives emerging leaders exposure to Responsible AI in practice. The field of AI is changing rapidly, making the need for responsible AI greater than ever. While only 18% of data science students reported learning about ethics in a recent industry survey, examples of AI products with unintended negative consequences continue to grow. Marisa Tricarico, the North America Practice Lead for Responsible AI at Accenture, has a unique perspective on the rapid expansion of this field, as she works with a growing roster of Accenture clients as they develop and deploy AI. Marisa and Accenture's work intersects with AI4ALL's work to train the next generation of responsible AI leaders as well.

Robot-led automation has the potential to transform today's workplace as dramatically as the machines of the Industrial Revolution changed the factory floor. Both Robotic Process Automation (RPA) and Intelligent Automation (IA) have the potential to make business processes smarter and more efficient, in very different ways. Both have significant advantages over traditional IT implementations. Robotic process automation tools are best suited for processes with repeatable, predictable interactions with IT applications. These processes typically lack the scale or value to warrant automation via IT transformation.

Disruptive new technologies and methodologies have already gained a foothold in most organizations. Cloud, Machine Learning, Edge Computing, IoT, Cybersecurity Best Practices, Additive Manufacturing, Augmented Reality, DevOps and more are enabling new business processes and obscuring traditional functional boundaries. OT, IT, and ET teams are growing their skills and capabilities and transforming real-time operations. Executives charged with driving transformation are seizing this moment to innovate and deliver real value. By using data, digital technologies, and machine learning, organizations can ask questions about their interactions with customers, then map those learnings back to how assets are deployed and managed in operations.

Deloitte announced a collaboration today with Automation Anywhere to drive further adoption of cloud deployments on Automation 360, the first cloud-native, AI-powered robotic process automation (RPA) platform. Deloitte will combine its leading capabilities in cloud infrastructure and automation to provide a first-of-its-kind solution that enables a successful migration of client automations to the cloud, helping organizations accelerate the rate and delivery of business performance while effectively limiting costs. Mutual customers, both first-time RPA and existing Automation Anywhere users, will experience a smooth transition to the cloud platform with Deloitte's migration as a service capabilities. "The need for digital transformation is more prevalent than ever as organizations continue to navigate the effects of the pandemic and pivot to cloud-based solutions that can seamlessly integrate with their existing systems," said Douglas Williams, managing director, Deloitte Consulting LLP. "Our solutions are designed for Automation 360 to help customers through the migration process to get the most value out of their RPA investment with minimal disruption, all while finding efficiencies and reducing investment costs."

Engineers and computer scientists spent decades perfecting computers' abilities to solve classical math and logic problems. But as it would turn out, a huge set of real-world decision-making isn't readily framed as a tidy math problem. Machine learning (ML) earns its paycheck in these kinds of situations: When we're unable to logically or cost-effectively use math to tell a computer what to do, we can use ML to teach a computer what to do by showing it examples of how it's been done. This current AI/ML "Cambrian explosion" is resulting in a radical rethink of what computers can realistically learn. Startups and incumbents alike are teaching machines to emulate an ever-increasing share of capabilities once thought of as "uniquely human." Other frontiers of AI advancement include sensation and discernment (the five "senses"); creativity (reading, writing, and the arts); and congeniality (emotional intelligence).

PwC announced that it was cited as a Leader in The Forrester Wave: AI Consultancies, Q1 2021. In the report, Forrester notes that "AI consultancy customers should look for providers that: Commenting on PwC, the report states that: "The PwC backstory has two facets -- client transformations and its own. PwC helps transform client businesses, but its own transformation is part of its story. PwC doubled down on its own upskilling and IP-building platform and then launched this for clients. One-off simulation projects are now scaled offerings for strategic planning, operations, and continuous scaling of business models. Even strategic innovation partnerships are points of excellence; one client specifically selected PwC because of the consultancy's relationship with Carnegie Mellon."

IDSIA has a very broad range of research interests, spanning most of Artificial Intelligence as it is understood today: machine learning, including deep learning/neural networks, control and signal processing, natural language processing, robotics, computer vision, search and optimisation, and more fundamental questions in uncertainty, probability, statistics, causal inference. To give an example, we have a 4-year Data project funded by the National Science Foundation as part of Switzerland's National Research Programme 75 "Big Data". In this project we deal with Gaussian processes, which can be understood as statistical neural networks, which can then provide uncertainty estimates relating to their own predictions – unlike traditional neural nets. This is very important in applications where we are evaluating risks. For example, a self-driving car needs to know whether the car's sensors are reliably warning of a potential accident ahead rather than a a person safely crossing the street.

I joined the Technology Research & Development team from Advanced Technology & Architecture where I was the global lead for Emerging Technology. I have held several global leadership roles within our technology group for Application Portfolio Optimization and SOA/Integration Architecture. I have worked at the leading edge of technology, notably in voice recognition, knowledge-based systems and neural networks.

The AI industry is playing a dangerous game right now in its embrace of a new generation of citizen developers. On the one hand, AI solution providers, consultants, and others are talking a good talk around "responsible AI." But they're also encouraging a new generation of nontraditional developers to build deep learning, machine learning, natural language processing, and other intelligence into practically everything. A cynic might argue that this attention to responsible uses of technology is the AI industry's attempt to defuse calls for greater regulation. Of course, nobody expects vendors to police how their customers use their products.

Apple's been on a shopping spree in a bid to make Siri smarter, according to a new report by GlobalData. The market research firm says the tech giant bought more AI companies than anyone else between 2016 and 2020. The second biggest AI acquirer was Irish consultancy Accenture. But the rest of the top five were all based in the US. Google grabbed the third spot on the list, followed by Microsoft and Facebook.