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AI safety tools can help mitigate bias in algorithms

#artificialintelligence

Where does your enterprise stand on the AI adoption curve? Take our AI survey to find out. As AI proliferates, researchers are beginning to call for technologies that might foster trust in AI-powered systems. According to a survey conducted by KPMG, across five countries -- the U.S., the U.K., Germany, Canada, and Australia -- over a third of the general public says that they're unwilling to place trust in AI systems in general. And in a report published by Pega, only 25% of consumers said they'd trust a decision made by an AI system regarding a qualification for a bank loan, for example.


AI Is A Game Changer: PWC AI Predictions Report

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AI is a major game changer. AI could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption side effects. Pricewaterhouse Cooper's (PwC) third annual AI Predictions Report has highlighted the importance of focusing on the fundamentals in preparation for large-scale AI projects. One of the big questions in their recent report was analyzing over 1000 respondents (200 CEOs) in the USA Survey and asked: How far along are companies in their usage of AI?


The State of AI Ethics Report (January 2021)

arXiv.org Artificial Intelligence

The 3rd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in AI Ethics since October 2020. It aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the field's ever-changing developments. Through research and article summaries, as well as expert commentary, this report distills the research and reporting surrounding various domains related to the ethics of AI, including: algorithmic injustice, discrimination, ethical AI, labor impacts, misinformation, privacy, risk and security, social media, and more. In addition, The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments. Unique to this report is "The Abuse and Misogynoir Playbook," written by Dr. Katlyn Tuner (Research Scientist, Space Enabled Research Group, MIT), Dr. Danielle Wood (Assistant Professor, Program in Media Arts and Sciences; Assistant Professor, Aeronautics and Astronautics; Lead, Space Enabled Research Group, MIT) and Dr. Catherine D'Ignazio (Assistant Professor, Urban Science and Planning; Director, Data + Feminism Lab, MIT). The piece (and accompanying infographic), is a deep-dive into the historical and systematic silencing, erasure, and revision of Black women's contributions to knowledge and scholarship in the United Stations, and globally. Exposing and countering this Playbook has become increasingly important following the firing of AI Ethics expert Dr. Timnit Gebru (and several of her supporters) at Google. This report should be used not only as a point of reference and insight on the latest thinking in the field of AI Ethics, but should also be used as a tool for introspection as we aim to foster a more nuanced conversation regarding the impacts of AI on the world.


Only 6% of companies have adopted AI, study finds

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In a new survey of over 700 C-suite executives and IT decision-makers examining AI adoption in the enterprise, Juniper Networks found that 95% of respondents believe their organization would benefit from embedding AI into their daily operations. However, only 6% of those respondents reported adoption of AI-powered solutions across their business. The findings agree with other surveys showing that, despite enthusiasm around AI, companies struggle to deploy AI-powered services in production. Enterprise use of AI grew a whopping 270% over the past several years, Gartner recently reported, while Deloitte says 62% of respondents to its corporate October 2018 study adopted some form of AI, up from 53% in 2019. But adoption doesn't always meet with success, as the roughly 25% of businesses that have seen half their AI projects fail will tell you.


Deloitte partnering with NVIDIA to launch artificial intelligence computing center

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Deloitte has launched the Deloitte Center for AI Computing, designed to accelerate the development of artificial intelligence offerings for its clients. The center is built on NVIDIA's DGX A100 systems to create a supercomputing architecture that will help Deloitte's clients in their efforts to become AI-fueled organizations. The accelerated computing platforms feature NVIDIA graphics processing unit technology, along with its networking and software for advanced data processing, analytics and AI by bringing massive parallel processing capability and speed to deep learning, machine learning and data science workloads, the company said. Deloitte's State of AI in the Enterprise survey found that more than half of respondents reported spending more than $20 million over the past year on AI technology and talent. Nearly all adopters said they were using AI to improve efficiency, while mature adopters are also harnessing the technologies to boost differentiation.


The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers

arXiv.org Artificial Intelligence

In many labor markets, workers and firms are connected via affiliative relationships. A management consulting firm wishes to both accept the best new workers but also place its current affiliated workers at strong firms. Similarly, a research university wishes to hire strong job market candidates while also placing its own candidates at strong peer universities. We model this affiliate matching problem in a generalization of the classic stable marriage setting by permitting firms to state preferences over not just which workers to whom they are matched, but also to which firms their affiliated workers are matched. Based on results from a human survey, we find that participants (acting as firms) give preference to their own affiliate workers in surprising ways that violate some assumptions of the classical stable marriage problem. This motivates a nuanced discussion of how stability could be defined in affiliate matching problems; we give an example of a marketplace which admits a stable match under one natural definition of stability, and does not for that same marketplace under a different, but still natural, definition. We conclude by setting a research agenda toward the creation of a centralized clearing mechanism in this general setting.


Deloitte State of AI in the Enterprise 2020

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Where do you stack up against your competitors when it comes to your AI initiative? Deloitte has released its 2020 State of AI in the Enterprise report which found only 47% say that they have a high level of skill around selecting AI technologies and suppliers. Deloitte's third edition of the "State of AI in the Enterprise" survey, conducted between Oct. and Dec. 2019, finds businesses are entering a new chapter in AI implementation where early adopters may have to work harder to preserve an edge over their industry peers. The study shows that companies at the top will be those that utilize AI to pursue creative and novel applications, actively address inherent AI risks and -- as more organizations buy AI-powered capabilities -- become smarter consumers of AI technology. "Seasoned" adopters are the example to follow as the global survey of 2,737 information technology and line-of-business executives finds this category has undertaken many AI production deployments.


How to hang on to AI's advantage

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As businesses use artificial intelligence to respond to the pandemic, 2020 marks the start of a mainstream AI adoption era in the enterprise. The technology, in physical and digital form, will couple with human teams to elevate their efficiency, while AI will touch practically every software platform involved in daily work. This is the reality portrayed in Deloitte's State of AI in the Enterprise report, a global survey of 2,700 IT and line of business executives released Tuesday. Three-quarters of AI-adopters expect the technology will be integrated into all enterprise applications in the next three years. For 73% of respondents, deployment of AI within their technology ecosystem is currently "very" or "critically" important to their business.


Human AI collaboration

#artificialintelligence

The wait is over: artificial intelligence (AI) is here. And despite apocalyptic predictions about workers being replaced by intelligent machines, leading organizations are taking a new tack: actively searching for strategies to integrate AI into teams to produce transformative business results. These "superteams" hold the promise of enabling organizations to reinvent themselves to create new value and meaning, while giving workers the potential to reinvent their careers in ways that help increase their value to the organization and their own employability. For organizations that still view AI mainly as an automation tool to reduce costs, connecting their AI initiatives with their efforts to craft more effective teams is a first step toward enabling humans and machines to work together in new, more productive ways. The Readiness Gap: Fifty-nine percent of organizations say the redesign of jobs to integrate AI technology is important or very important for their success over the next 12 to 18 months, but only 7 percent say they are very ready to address this trend.


Ethical implications of AI and the future of work

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As the future of work rapidly evolves, and organizations are integrating people, technology, alternative workforces, and new ways of working, leaders are wrestling with an increasing range of resulting ethical challenges. These challenges are especially pronounced at the intersection between humans and technology, where new questions have risen to the top of the ethics agenda about the impact of emerging technologies on workers and society. How organizations combine people and machines, govern new human-machine work combinations, and operationalize the working relationship between humans, teams, and machines will be at the center of how ethical concerns can be managed for the broadest range of benefits. Organizations that tackle these issues head-on--changing their perspective to consider not only "could we" but also "how should we"--will be well positioned to make the bold choices that help to build trust among all stakeholders. The Readiness Gap: Seventy-five percent of organizations say ethics related to the future of work are important or very important for their success over the next 12 to 18 months, but only 14 percent say they are very ready to address this trend.