Cognitive Science

In the 1970s and '80s, he was part of a small cohort of organizational behaviorists who argued that just focusing on skills in the workplace wasn't enough. Instead, they insisted that an individual's competencies must be assessed and reinforced. People [in the field] said it's all knowledge, skills and abilities. But a few of us kept arguing that there was a behavioral level they weren't tapping with skills, that skills were too micro." Today, he proudly notes, "there's hardly a human resources organization serving 100 or more people that doesn't use competency language."

Artificial Intelligence (AI) is going through the process of evolution. To date we have seen the emergence of artificial narrow intelligence (ANI), and artificial general intelligence (AGI) to artificial super intelligence (ASI). Those working in the field predict that it won't be long until AI is able to "combine the intricacy and pattern recognition strength of human intelligence with the speed, memory and knowledge sharing of machine intelligence," as Jayshree Pandya writes in his recent Forbes article. One of the upshots of this progress is that people feel less insecure and fear what this may mean for their future, particularly with regard to employment. After all if AI can replace most manual and mundane work that will affect a significant number of people in manufacturing industries.

Data has become the most valuable currency in business. But without the right tools or intelligence, its true value will not be realised. According to a MiQ survey, 43 per cent of US and UK brand marketers think that the lack of measurement of business impact, such as sales or growth, is the main hurdle to investing more in data analytics. But if marketing metrics are not the same as business goals, why are campaigns measured against them? Marketing should align with the same goals as the rest of the company, in order to measure tangible business results.

In the early 1990s, Lisa Feldman Barrett had a problem. She was running an experiment to investigate how emotions affect self-perception, but her results seemed to be consistently wrong. She was studying for a PhD in the psychology of the self at the University of Waterloo, Ontario, Canada. As part of her research, she tested some of the textbook assumptions that she had been taught, including the assumption that people feel anxiety or depression when, despite living up to their own expectations, they do not live up to the expectations of others. But after designing and running her experiment, she discovered that her test subjects weren't distinguishing between anxiety and depression.

The big day has come: You are taking your road test to get your driver's license. As you start your mom's car with a stern-faced evaluator in the passenger seat, you know you'll need to be alert but not so excited that you make mistakes. Even if you are simultaneously sleep-deprived and full of nervous energy, you need your brain to moderate your level of arousal so that you do your best. Now a new study by neuroscientists at MIT's Picower Institute for Learning and Memory might help to explain how the brain strikes that balance. "Human beings perform optimally at an intermediate level of alertness and arousal, where they are attending to appropriate stimuli rather than being either anxious or somnolent," says Mriganka Sur, the Paul and Lilah E. Newton Professor in the Department of Brain and Cognitive Sciences.

The Pentagon's research arm is looking beyond the human brain to build artificial intelligence. In a recent call for submissions, DARPA revealed that it's looking for ways to take the brains of'very small flying insects' and model their functions in AI robots. The proposal looks to pave the way for robots that are smaller, energy-efficient and easier to train. DARPA is looking beyond the human brain to build artificial intelligence. In a call for proposals, it revealed that it's looking for ways to take insect brains and model their functions in AI robots DARPA is looking for proposals that understand the sensory and nervous systems in miniature insects and can turn them into'prototype computational models.'

Humans retrieve the memory of an event in reverse to how they saw it, a report published today has discovered. Instead of constructing a past memory by building a picture from details of the event, the brain forms an overall'gist' of what happened first. It then fills out the story by retrieving more detail. This process seems to be the opposite of how the brain works when first encountering an event. The latest findings may give scientists greater insight into the reliability and accuracy of memory and witness accounts of incidents such as crime.

In the popular TV show Sherlock, visual depictions of our hero's deductive reasoning often look like machine algorithms. And probably not by accident, given that this version of Conan Doyle's detective processes tremendous amounts of observed data--the sort of minutiae that the average person tends to pass over or forget--more like a computer than a human. Sherlock's intelligence is both strength and limitation. His way of thinking is often bounded by an inability to intuitively understand social and emotional contexts. The show's central premise is that Sherlock Holmes needs his friend John Watson to help him synthesize empirical data into human truth.

A research collaboration headed up at the National University of Singapore (NUS) has successfully employed machine learning to investigate the cellular architecture of the human brain. The approach uses functional MRI (fMRI) data to automatically estimate brain parameters, enabling neuroscientists to infer the cellular properties of different brain regions without having to surgically probe the brain. The researchers say that their technique could potentially be used to assess treatment of neurological disorders or develop new therapies (Science Advances 10.1126/sciadv.aat7854). "The underlying pathways of many diseases occur at the cellular level, and many pharmaceuticals operate at the microscale level," explains team leader Thomas Yeo. "To know what really happens at the innermost levels of the human brain, it is crucial for us to develop methods that can delve into the depths of the brain non-invasively." Currently, most human brain studies employ non-invasive approaches such as MRI, which limits examination of the brain at a cellular level.

Is AI going to displace workers or come as a benefit to them?Getty Smart technologies aren't just changing our homes; they're edging their way into their numerous industries and are disrupting the workplace. Artificial Intelligence (AI) has the potential to improve productivity, efficiency and accuracy across an organization – but is this entirely beneficial? Many fear that the rise of AI will lead to machines and robots replacing human workers and view this progression in technology as threat rather than a tool to better ourselves. With AI continuing to be a prominent buzzword in 2019, businesses need to realize that self-learning and black-box capabilities are not the panacea. Many organisations are already beginning to see the incredible capabilities of AI, using these advantages to enhance human intelligence and gain real value from their data.