Articles by Sue Feldman
Cognitive computing and AI begin to grow together
How do we manage the hype and promise for new inventions while making sure that they represent a realistic opportunity? Can we invent self-driving cars or a Boeing 737 MAX without exposure to the risks these innovations can pose to our lives?
Ethical issues in AI and cognitive computing
Many innovations from the past needed the insight of entrepreneurs as well as technologists to change the world. That's also the case with machine learning and AI.
Usability testing for effective interactivity
Connecting the seeker to the information she seeks is not a new problem. Interaction design has been a stumbling block since the age of the card catalog.
Cognitive Computing: Balancing the risks with the rewards from AI
The fact is that the effects of AI and cognitive computing will be even broader than current traditional computing systems. As we incorporate more and more data sources for better results, we also increase the likelihood of affecting more lives and more organizations.
Using AI in an uncertain world
Human thinking balances AI systems. They can plug each other's blind spots. Humans make judgments based on their worldview. They are capable of understanding priorities, ethics, values, justice and beauty. Machines can't. But machines can crunch vast volumes of data.
Psychographics, statistics and Big Brother
The fact is that any of the techniques available to the market today for predicting one's actions based on a profile can be important tools, but they cannot, with any great accuracy, predict the behavior of one single individual. They rely on groups of similar individuals to predict the probability of one person's actions.
Cognitive applications in real life
We see threat detection emerging as the first cognitive computing application to become prevalent. Major banks, credit risk companies, government customs organizations or security agencies are all investing in cognitive computing because they cannot keep up with the onslaught of data, particularly text.
Picked up from the podium
Artificial intelligence is a large umbrella term that includes: machine learning of all types, digital assistants, conversational systems, Internet of Things, image and speech recognition, emotion and sentiment detection, cognitive computing, robotics and more.
Cognitive computing: Strategies for survival
The fact is that we are awash in data.
What makes a computer system cognitive?
Cognitive computing systems address complex situations that are characterized by ambiguity and uncertainty—in other words, human kinds of problems. In those dynamic, information-rich and shifting situations, data tends to change frequently, and it is often conflicting. The goals of users evolve as they learn more and redefine their objectives.
Need a digital assistant?
By amassing more information than any of us can individually, and then presenting it in an analytic environment with our problem as the lens, a cognitive app can encourage the intuition and creative imagination of the human expert. Cognitive computing augments the human capacity for taking in random information and combining it in novel ways within the context of a current problem....
Cognitive computing: A definition and some thoughts
Computers are one of those artifacts of modern life that we love to hate. They are powerful, pervasive, intrusive and, let's face it, clumsy to use. Today's applications require us to break down complex, subtle ideas into simplistic statements. We must learn arcane codes to speak their language. They are incapable of assisting us in an evolving knowledge voyage because their understanding breaks down as our context or intentions change.
Cognitive computing: Beyond the hype
Cognitive computing should redefine the relationship between people and their digital environment. Context is the new element at the heart of this next computing frontier....
What Makes Search Great?
A great search solution requires more than a search engine. Search engines are useful technologies. But to transform a technology into something...
What are people searching for and where are they looking?
We know that knowledge workers spend a large percentage of their time looking for information. What are they looking for and where are they looking? In fall 2007, we set about trying to find out. In conjunction with KMWorld and IDC's Technology Advisory Panel, we asked participants to tell us how long they spent searching, what their typical questions were, and where they went (online or print) to find the information they needed.
Search: an interesting muddle
Desperately seeking search
The high cost of not finding information