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AI for business gets boost with new IBM Watson tech

AI for business: Project Debater
The Project Debater AI was not only a good debater, but also an aspiring comedian

Natural Language Processing (NLP) is hardly elementary for AI for business. IBM Watson, however, will now have a better understanding of the language of business. This is thanks to the incorporation of new technologies from IBM Research’s Project Debater.

Project Debater made headlines in 2018 when the IBM AI successfully debated humans and even made jokes. The new IBM Watson technologies represent the first commercialization of Project Debater’s groundbreaking NLP abilities. Now companies can reap the benefits of an AI for business that understands idioms and colloquialisms in conversational English. IBM Watson will not just analyze human language for information. It can now also understand the thought and opinion of customers. This is in line with IBM’s vision for the relationship between humans and AI in the workplace.

Understanding human subjectivity

“This combination of human and machine makes AI both powerful and transformative. It’s why IBM refers to AI as augmented—not artificial—intelligence. This is a critical difference. IBM believes in systems that can enhance and scale human expertise, rather than those that attempt to replicate human cognition,” IBM Philippines Chief Technology Officer Lope Doromal Jr. told Digital Life Asia via email.

Project Debater’s story started in 2012. A team of researchers in Israel started working on a new kind of AI. Their efforts took AI to uncharted territory—the world of human discourse. As the above trailer put it:

“We have to step away from games. We have to step away from black and white challenges. So, AI is now going to deal with the subjectivity of human reality.”

With Project Debater technologies now incorporated into IBM Watson, enterprises can gain a competitive advantage. They can now do things that no other AI system is capable of today.

“IBM is leading the way in advancing breakthroughs in this field of NLP, infusing these technologies into a widening portfolio of Watson products, including Watson Assistant, Watson Discovery and Watson Natural Language Understanding.

“Businesses now have the ability to identify, understand and analyze idioms—phrases that can have distinctive, but sometimes unintuitive meanings, like ‘over the moon’, ‘hardly helpful’, ‘cold feet’, and ‘I’m all ears’. For example, the phrase ‘over the moon’, might be interpreted as literally above the planetary satellite and not ‘excited’ or ‘elated’. With Project Debater’s core AI built into IBM Watson, AI can understand such an idiom,” Doromal said.

AI beyond customer care

One area where an AI for business with NLP mastery can have an immediate impact is customer care. Casual language used to make it challenging for AI to understand, classify, and conduct a fine-grained analysis of human conversations.

Beyond customer care, however, AI can now analyze the vast stores of data in human language that businesses have accumulated.

“For example, let’s say that a local government needs to make a decision on whether the city should invest in autonomous vehicles. Humans make decisions based on pros and cons. With this capability, AI can sift through huge amounts of different sources of data to extract and assess arguments for and against the proposal. The local government can then use the results to help make a policy decision,” Doromal said.

Doromal acknowledged that AI’s human colleagues will also need to adapt to a changing workplace.

“IBM is leading efforts to ensure workers worldwide are prepared for data-driven changes that are reshaping how work gets done, and that are driving productivity, economic growth, and job creation. We are working with policymakers to modernize education systems to emphasize in-demand skills rather than specific academic degrees, preparing more workers for new collar jobs,” he said.

Algorithms and human biases

One of the concerns over AI is that they might bake in and scale human biases. As McKinsey Global Institute pointed out in the article:

“Two opportunities present themselves in the debate. The first is the opportunity to use AI to identify and reduce the effect of human biases. The second is the opportunity to improve AI systems themselves, from how they leverage data to how they are developed, deployed, and used, to prevent them from perpetuating human and societal biases or creating bias and related challenges of their own. Realizing these opportunities will require collaboration across disciplines to further develop and implement technical improvements, operational practices, and ethical standards.”

Doromal said IBM is making sure that biases will not creep into their algorithms. He again stressed the cooperation between humans and AI for decision-making.

“We firmly believe that artificial intelligence cannot and will not replace human decision-making, judgment, intuition, or ethical choices. Companies must be able to explain what went into their algorithm’s recommendations. If they can’t, then their systems shouldn’t be on the market. IBM therefore supports transparency and data governance policies that will ensure people understand how an AI system came to a given conclusion or recommendation. As society debates the implications of AI systems, IBM opposes efforts to tax automation or penalize innovation.

“Trust is essential to AI adoption. IBM Research has pioneered a Trusted AI infrastructure based on five core components— fairness, explainability, robustness (or security), transparency and accountability, and value alignment—woven into the lifecycle of an AI application.”

Who’s afraid of AI?

Thanks largely to science fiction, many people are afraid of AI. For instance, some worry that it could become sentient and decide to wipe out humanity. Skynet, anyone?

In particular, Elon Musk has been very vocal about expressing his fears. You can even read about it his biography, “Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future“. In the book, he said he was terrified of what his friend, Google Co-Founder Larry Page, was doing with AI.

“Here’s Vance’s account of a conversation he had over dinner with Musk, as it appears in the book:

“He opened up about the major fear keeping him up at night: namely that Google’s cofounder and CEO Larry Page might well have been building a fleet of artificial intelligence-enhanced robots capable of destroying mankind. ‘I’m really worried about this,’ Musk said. It didn’t make Musk feel any better that he and Page were very close friends and that he felt Page was fundamentally a well-intentioned person and not Dr. Evil. In fact, that was sort of the problem. Page’s nice-guy nature left him assuming that the machines would forever do our bidding. ‘I’m not as optimistic,’ Musk said. ‘He could produce something evil by accident.'”

Why AI will make us better humans

Doromal, however, believes that AI for business will help humans make better decisions and do their jobs well. He sees a world transformed for the better by AI for business.

“There is no question AI will inspire significant shifts in our workforce, creating entirely new types of work, occupations, and opportunities. Gartner predicted that by 2020, AI will become a positive net job motivator, creating 2.3 million jobs while eliminating only 1.8 million jobs. We’ve already seen instances where professionals—chemists, researchers, doctors, financial analysts—are finding AI technologies are helping them immensely in doing their jobs better.

“The real risk to society is the price of not knowing. Every day we pay the price for not knowing what’s wrong with a patient, not knowing where to find critical natural resources, or not knowing where the risks lie in our global economy. AI promises a new level of collaboration between man and machine and will only augment and expand human intelligence, not replace it,” Doromal said.

After all, ignorance may be bliss, but it is not good for business. Or for the future of humanity.


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