Machine Learning

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Justifying Human Involvement in the AI Decision-Making Loop

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Though AI is far from perfect, vast training data has given smart systems formidable accuracy in making independent decisions. Yet even as these decision-making capabilities improve, a Cold War history lesson reminds us that human involvement may still be needed to avoid intolerable consequences of incorrect AI decisions.

Five Management Strategies for Getting the Most From AI

A global survey by the McKinsey Global Institute finds that AI is delivering real value to companies that use it across operations. C-level executives report that when they adopt AI at scale — meaning they deploy AI across technology groups, use AI in the most core parts of their value chains, and have the full support of their executive leadership — they are finding not just cost-cutting opportunities, but new potential for business growth, too.

Sponsor's Content | Journey to AI: Building a Foundation in Big Data Analytics

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AI is making headlines — and not just in futuristic technologies like self-driving cars. It’s transforming business processes in established industries, from retail to financial services to manufacturing. But what’s the best way to adopt AI for your organization?

Reshaping Business With Artificial Intelligence

Disruption from artificial intelligence (AI) is here, but many company leaders aren’t sure what to expect from AI or how it fits into their business model. Yet with change coming at breakneck speed, the time to identify your company’s AI strategy is now. MIT Sloan Management Review has partnered with The Boston Consulting Group to provide baseline information on the strategies used by companies leading in AI, the prospects for its growth, and the steps executives need to take to develop a strategy for their business.

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Accelerate Access to Data and Analytics With AI

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Detailed and data-rich insights won’t help your company if your employees don’t know where to find them — but that’s a problem AI can solve. Machine learning can enable faster organizational learning by helping each employee quickly understand what others in the organization understand — forming a knowledge distribution network.

Ethics Should Precede Action in Machine Intelligence

As analytics and big data continue to be integrated into organizational ways and means from the C-suite to the front lines, authors Josh Sullivan and Angela Zutavern believe that a new kind of company will emerge. They call it the “mathematical corporation” — a mashup of technology and human ingenuity in which machines delve into every aspect of a business in previously impossible ways.

How Big Data Is Empowering AI and Machine Learning at Scale

Big Data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the coming decade. Organizations are now combining the agility of Big Data processes with the scale of AI capabilities to accelerate the delivery of business value.

AI and the Need for Speed

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AI is rapidly changing how organizations make decisions, serve customers, increase quality, and reduce costs. But the pace of change may be too fast for managers to effectively manage processes, react to new problems, and learn from data whose usefulness has a shorter and shorter lifespan.

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Companies Brace for Decade of Disruption From AI

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With investments in Big Data bearing fruit, what do executives expect from the future? A new survey finds that artificial intelligence and machine learning are rapidly emerging avenues for innovation — and disruption. Nearly half of senior executives surveyed, from companies like American Express, Disney, Ford Motors, and General Electric, see disruptive change coming fast.

Digital Today, Cognitive Tomorrow

Digital transformation is happening all around us, but it’s the foundation for a much more profound transformation still to come. With huge challenges facing humanity on many fronts — climate, disease, population, food and water — we need cognitive technologies to augment human problem-solving capabilities. And those technologies are almost here.

When Machine Intelligence Meets Main Street

We are past the point of debating whether human intuition can be replicated. Machine learning is already here. It will impact most companies over the next few decades and become part of everyday business life. Executives must quickly come to grip with how companies and industries will evolve.

The Shifts — Great and Small — in Workplace Automation

Despite valid concerns about machines displacing workers, human labor isn’t going away any time soon. Tasks that cannot be substituted by automation are generally complemented by it. Still, while automation does not reduce the quantity of jobs, it may greatly affect the quality of available jobs. For workers to benefit from IT, human-capital investment must be at the heart of any long-term strategy for producing skills that are complemented, rather than substituted, by technological change.

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Want to Improve Your Portfolio? Call a Scientist

In a conversation with MIT SMR’s David Kiron and Sam Ransbotham, associate professor of information systems at the Carroll School of Management at Boston College and guest editor for the Data and Analytics Big Idea Initiative for the MIT Sloan Management Review, Jeffrey Bohn, chief science officer at State Street Global Exchange discusses how he is developing better trading and risk strategies for clients using State Street’s proprietary data and analytics.

Sales Gets a Machine-Learning Makeover

New advances in machine learning are allowing sales teams to manage huge amounts of data to become more effective and efficient. Our research suggests three main ways machine learning is being successfully integrated into sales processes. First, it allows for a scientific approach that clarifies opaque parts of the sales process. Second, it enables more-effective data-driven experimentation. Third, it automates administrative duties that take time away from higher-value tasks.

Showing 1-18 of 18