If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
I first started working in the world of virtual agents in 2000 and, even though the technology was very much in its infancy at the time, saw huge potential for innovation and growth in the industry. Having now led my own company in this space for over 15 years, I have a unique perspective on the advancements of conversational AI technology and the ways it can be used. I was pleased to share some of my insights with the AI Time Journal recently in an interview for their Conversational AI Initiative. Whether you use chatbots, virtual agents, conversational AI or one of the other numerous terms in the market today to describe this technology, one of the biggest challenges the industry faces (besides the inconsistent terminology!) is the lack of understanding within organisations about deploying these solutions. Just a few years ago this was due to them not really knowing much about virtual agents or how these tools can be used to improve the customer and employee experience.
Facial mapping example used to construct a deepfake video. As society increasingly wrestles with the impact of "deep fakes" it is important to acknowledge that much of the current hype is overstated. While it is true that deep fakes constitute an important future issue, today's tools are far less developed or user-friendly than the breathless media hype and public fears might suggest. Most importantly, in many ways the rise of deep fakes mirrors the rise of Photoshop nearly 30 years ago, with a rise in falsified images met with increasing scrutiny of image-based evidence. While deep learning approaches promise higher-quality falsifications with greater ease, if Photoshop did not lead us to abandon our trust in images, do deep fakes really represent the threat we believe they do?
Artificial intelligence (AI) has been the most far-flung goal of mankind since the birth of the computer. However, we can certainly say that we are closer to that goal than ever with the advent of new cognitive computing models. In a layman's terms, cognitive computing is a mashup of cognitive science and computing science, where cognitive science studies the human brain and how it works and computing science deals with the innovative ways of using computers for the betterment of the community. Cognitive computing systems are used to find solutions to complex situations where answers are uncertain or ambiguous, using computerized models that simulate the human cognition process. Although the term is often used alongside AI, it is closely related to Watson, IBM's cognitive computer system.
The Institute for the Future (IFTF) in Palo Alto, CA, is a U.S.-based think tank. It was established in 1968 as a spin-off from the RAND Corporation to help organizations plan for the long-term future. Roy Amara, who passed away in 2007, was IFTF's president from 1971 until 1990. Amara is best known for coining Amara's Law on the effect of technology: "We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run." This law is best illustrated by the Gartner Hype Cycle,a characterized by the "peak of inflated expectations," followed by the "trough of disillusionment," then the "slope of enlightenment," and, finally, the "plateau of productivity."
There's a lot of hype about AI right now, and while it's a fundamental tool, the adoption of AI is exaggerated. When most people think of AI, they think of robots. But, in reality, AI consists of algorithms that conduct systems like data processing, that are too bulky and time-consuming for human capabilities. Despite not being widely adopted yet, the future belongs to AI because it enables business systems to operate with granular precision and scalability that simply isn't possible at a human level. The caveat: AI cannot completely replace human input.
Few ideas in the last decade have provoked as much excitement, or as much confusion, as the introduction of artificial intelligence (AI) in oncology. From the first moment we announced our plans to apply our Watson technology to help oncologists, we were met with a stark dichotomy of emotion. The headlines ran the spectrum from hype (your next doctor might be a robot!) to cynicism (5 reasons AI in healthcare will fail). Today, five years into the journey to help improve cancer treatment through data, analytics and AI, while we're still very much in the early stages, I'm happy to report that the real-world progress is far more encouraging than either of those early storylines would suggest. In fact, not only is AI being used to support physicians in the delivery of cancer care today, it is producing quantifiable results while charting a course for the future.
"Artificial intelligence is among the most consequential issues facing humanity, yet much of today's commentary has been less than intelligent: awe-struck, credulous, apocalyptic, uncomprehending. Gary Marcus and Ernest Davis, experts in human and machine intelligence, lucidly explain what today's AI can and cannot do, and point the way to systems that are less A and more I." --Steven Pinker, Johnstone Professor of Psychology, Harvard University, and the author of How the Mind Works and The Stuff of Thought "Finally, a book that tells us what AI is, what AI is not, and what AI could become if only we are ambitious and creative enough. No matter how smart and useful our intelligent machines are today, they don't know what really matters. Rebooting AI dares to imagine machine minds that goes far beyond the closed systems of games and movie recommendations to become real partners in every aspect of our lives." Every CEO should read it, and everyone else at the company, too.
Artificial Intelligence (AI) and Machine learning (ML) are starting to feel a lot like the latest celebrity gossip--high on hype and light on substance. You can barely read a technology article or release today without someone espousing the latest AI/ML capabilities. The sales performance management (SPM) space, in particular, is one where the hype of AI/ML has not yet delivered on the hope of providing truly meaningful, actionable intelligence to customers--until now. Organizations must undergo a sales transformation to truly stay ahead in the fast-paced, competitive sales environment. It all comes back to the data, as well as access to vast computing power and readily available AI/ML algorithms.
AI isn't science fiction or a future technology we're waiting to adopt. It is, right now, affecting every aspect of our daily lives, and that includes how we develop applications, products, and services. Every few years, there's a new buzzword technology that drives mass hype as it promises to disrupt the status quo: software, mobile, IoT, 3D printing, virtual reality, blockchain. In 2016, every company desperately wanted to latch on to artificial intelligence (AI). So while the earliest innovators (think Alan Turing) were studying how computers could mimic humans in the 1950s, we just recently witnessed a hype cycle triggered by the potential for AI to cause the next generational shift in computing.
There is a lot of AI action in Aotearoa this year. Yes, Artificial Intelligence is a red-hot topic. Many-a-talk at Tech Week last week featured the topic of AI somewhere in the mix. Layered on top of all this is a decent dollop of AI-related media hype. Fair enough; there are some intriguing stories based on comments by thought leaders such as Stephen Hawkings and Elon Musk.