“Our tool turns complex data into intuitive 3-D shapes that can be visually examined and compared. Essentially, we are leveraging the visual system’s amazing ability to find patterns in the world around us to also find patterns in complex scientific data.” This research is from Dartmouth College, reported in a 7 May 2018 ScienceDaily paper, New software, HyperTools, transforms complex data into visualizable shapes. The paper also notes that “Techniques provide users with insights into high-dimensional datasets.”

 

The researchers demonstrate how HyperTools can be applied to various types of data. In the paper, they showcase visualizations of: brain activity, movie frames and brain responses to watching those frames; changes in temperature measurements across the Earth’s surface from 1875 to 2013; and the thematic content of political tweets issued by Hillary Clinton and Donald Trump during the 2016 US presidential campaign.

 

But Wait, There’s More

 

The insights revealed by the tool can also be used to guide the development of machine learning algorithms. For example, the data visualizations can reveal how different types of observations form structured distinct clusters (e.g. Trump tweets vs. Clinton tweets) that could be used to understand the similarities and differences between groups.

 

Coincidentally, in an 8 May 2018 ScienceDaily study from North Carolina State University,  ‘League of Legends’ to gain insights into mental models, “Psychology researchers have used the game League of Legends to advance our understanding of how people build ‘mental models’ — the mental tools that allow people to make use of complex systems.“  The lead author explains that “Our goal with this study was to get a deeper understanding of how people structure these mental models in their memories, and how those structures change as we gain expertise. In other words, how does the structure of a mental model differ between a novice, a journeyman and an expert?”

The study shows that expert mental models contain subnetworks which give “significant insights into the interconnection of myriad concepts.”

 

And it’s not just mental models. A 24 May 2018 ScienceDaily study from Drexel University, New parts of the brain become active after students learn physics, shows that parts of the brain not traditionally associated with learning science become active when people are confronted with solving physics problems.

 

Potential Risks?

 

Do the above HyperTools  or the ‘mental models’ raise any potential risks? We know that “the visual system’s amazing ability to find patterns in the world around us” can be fooled by optical illusions.

Our April 2018 article from The Conversation,  AI can help in crime prevention, but we still need a human in charge,  by David Tuffley, Griffith University, highlights the potential risks in a Human/AI partnership (including a replay of the glitch scene from the 1987 Robocop film.) For policing, that article suggests “The technology should always be subordinate to the human, taking the role of decision support helper.”

 

 

Perhaps a bigger area of risk is that raised in our July 2017 article from The Conversation, The future of artificial intelligence: two experts disagree. In that case, the experts disagreed on the unforeseen risks  posed by AI in terms of “The challenge is that with newly developing technologies, there is an illusion of 100% control, which doesn’t really exist.” On the other hand, the experts tended to agree that in the short to medium term, loss of jobs to AI might be significant where “occupations are easily automatable”, such as the construction industry.

 

However, a 23 May 18 ABC News report,  Robots creating a wages and employment ‘death spiral’ warns IMF,  gives the following Key points:

  • Workers are facing a “death spiral” of falling wages and rising inequality according to IMF report
  • Skilled wage could rise by 160pc and unskilled wages fall by 60 pc in worst case scenario
  • Conventional education and tax policies would have a limited impact in solving the problems”

 

The report’s first quote appropriated from management consultant, Warren Bennis, is.

The factory of the future will have only two employees, a man and a dog. The man will be there to feed the dog. The dog will be there to keep the man from touching the equipment.

 

On a brighter note, a 23 May 2018 report in The Guardian, Australia can be competitive car manufacturer again, says UK industrialist quotes Sanjeev Gupta whose company bought South Australia’s Whyalla’s steelworks:

“We will definitely in the next two or three years have a car in production in Australia,”

“It’s a very different way of thinking about cars, it’s a much cheaper way of making cars, and you can make them in a much smaller volume,

The Guardian report notes that Gupta “is also committed to increasing his company’s renewable energy production in Australia to 10 gigawatts to support his local ventures….His company also plans to build major battery storage facilities in Port Augusta and Whyalla”

 

Some further mixed news about AI comes in a  May 10, 2018 NYT article Alexa and Siri Can Hear This Hidden Command. You Can’t. and in a 24 May 2018 ScienceDaily study from University of British Columbia“Hey Alexa: Amazon’s virtual assistant becomes a personal assistant to software developers.”

The NYT article gives some interesting details on how the Researchers can now send secret audio instructions undetectable to the human ear to Apple’s Siri, Amazon’s Alexa and Google’s Assistant.   This topic is dissected in our article from The Conversation on May 10, 2018, by Richard Matthews, PhD Candidate, University of Adelaide, How silent signals from your phone could be recording and tracking you

The ScienceDaily study brings some good news for software engineers:

“Computer scientists have turned Amazon Alexa into a tool for software engineers, tasking the virtual assistant to take care of mundane programming tasks, helping increase productivity and speed up workflow.”

 

Tags: Dartmouth College, North Carolina State University, Drexel University, Educational Psychology, Computer Modeling, Artificial Intelligence, unemployment, robots-and-artificial-intelligenceAutomotive industry, Electric, hybrid and low-emission cars,  The Guardian, University of Adelaide, The Conversation, University of British Columbia, NYT,


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