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AI transforms work as we know it

Artificial Intelligence (AI) continues to disrupt industry and experts say that we need to focus on unique human skills.

A recent report by economics and strategy consulting firm AlphaBeta predicts that AI could replace 3 million Australian workers by 2030, based on the growing rate of job automation. They report that one third of the entire Australian workforce reportedly spent 70% of their time on automatable tasks, putting them most at risk of redundancy.

Professor Toby Walsh, a leading researcher in AI at UNSW and author of Android Dreams: The Past, Present and Future of AI, says that the consequences will be significant. “If we do nothing… a lot of people will be put out of work, and won’t have the skills for any of the new jobs that are created by technology.”

He says that as AI become more prevalent across all industries, we need to make significant societal changes to education, employment and taxation: “If we do, then the machines can take the sweat and we can focus on the finer things in life.”

AI is proving to be excellent in performing repetitive tasks which many of us find tiresome. Some of the innovations are particularly surprising. Lawyers are employing AI-assistants which laboriously scan legislation and case law for them. Doctors are digitising paperwork with data-processing tools, freeing up their time for patients. Even journalists could soon be using AI-driven fake news detectors to ensure accurate reporting.

Here are just a selection of the latest AI tools which are causing an industry upheaval in medicine, law and journalism.

Medicine: superhuman therapists to the rescue

New Scientist recently published an article declaring that AI will soon be a standard part of your medical care, heralding “the rise of the superhuman doctor”. According to Isaac Kohane, head of Biomedical Informatics at Harvard Medical School, AI is poised to change the very delivery of healthcare by equipping medical professionals with enhanced abilities.

IBM estimate that medical images currently account for at least 90% of human data. To save radiologists from repetitively viewing thousands of medical images, deep learning algorithms are being optimised for healthcare by companies such as IBM (Watson), the Fraunhofer Institute for Medical Image Computing (MEVIS) and GE Healthcare (Arterys). These tools carry out tasks such as detecting and tracking the progression of tumours, detecting diabetic retinopathy and diagnosing cardiovascular disease.

AI-based diagnostic and treatment-recommendation tools have attracted their fair share of controversy, with critics stating that they are expensive and time consuming to link with patient medical records. But AI developers are confident that AI is highly capable of improving health care. AI has the potential to ease the burden of administrative tasks, such as the digital form-filing of patient data. This frees up doctors to take more detailed patient histories and keep on top of the latest research.

Law: AI smooths out divorce and fights your parking fines for you

File this under one of the most unexpected automation processes you’ve ever heard of: www.wevorce.com is a self-guided divorce solution which has been developed to handle divorces more efficiently. After clients provide their information, it uses an algorithm to predict how the divorce will progress and then provides services based on the predictions. It’s just one example of the ways in which legal services are being disrupted by AI.

The world’s first AI lawyer, ROSS, is being used by US bankruptcy law firm BakerHostetler to digest thousands of pages of legal research. The Chief information officer, Bob Craig, refutes concerns that legal jobs will be taken over by AI. “ROSS is not a way to replace our attorneys – it is a supplemental tool to help them move faster”, he says. With AI capable of combing through hundreds of pages of case law, lawyers can then focus on tailoring legal solutions to their clients.

As AI increasingly spreads its roots in the legal sphere, there is a huge opening in the market for legal tech, according to Australian online legal publication BucketOrange.  Stanford Uni student Joshua Browder has created a “DoNotPay” chatbot which has successfully appealed thousands of parking tickets. As the potential for technologically advanced legal services grows, tech-minded law graduates will only find their career opportunities expanding.

Journalism: rise of the robot reporters

AI-driven tools could soon be assisting journalists with video production, compiling poll information (particularly during elections) and collecting information from on-the-ground sources at news events. Reporters are excited that AI could take over journalistic “grunt work”, freeing up journalists for more creative and complex assignments.

AI could also help fight “churnalism” (stories which are not properly fact-checked or researched). AI can already recognise basic storylines using natural language programming (NLP) techniques. The next step would be to sample a range of versions of a story from various sources, says Kurt Barling, Professor of Journalism at Middlesex University. Algorithms could then identify bias, which could be flagged by statements such as “you couldn’t make it up”. These tools could help journalists gauge the integrity of tweets and news alerts to nip the spread of fake news in the bud.

The Australian developed ClaimBuster uses NLP to identify factual claims within text, but is so far only used as a fact-checking tool by (human) journalists. Completely automated fact checkers, such as  Factmata, are still in development.

Nevertheless, the complete replacement of journalists by “robot reporters” remains highly unlikely, according to an Oxford University study. In a recent opinion piece for The Japan Times, the editor of Kyodo News wrote that although AI could take over simple announcements, it could never replace investigative reporting, provide deep analysis or produce emotional profile pieces.

The human advantage

Amongst all of these new innovations, it’s worth remembering that there are aspects of every job that AI will never be able replace. Walsh believes that “to stay ahead of the machines, we need to focus on areas where humans have an edge”. This includes creativity, emotional intelligence and the ability to make the right judgment under pressure: human capacities which will remain valued in every role.

– Larissa Fedunik

New science magazine INGENUITY launched

Featured image above: At the launch of INGENUITY with UNSW Dean of Engineering Mark Hoffman, Refraction Media cofounders Karen Taylor-Brown and Heather Catchpole, and UNSW Engineering’s senior communications advisor Wilson da Silva

INGENUITY, a new science magazine focusing on the frontiers of engineering research at UNSW and with a global distribution, was launched on Tuesday by UNSW’s Dean of Engineering, Mark Hoffman.

“We are, without question, a powerhouse of engineering research in Australia,” said Hoffman. “With nine schools, 32 research centres and participating or leading 10 Cooperative Research Centres, we do truly amazing research – among the world’s best. And we work with more than 500 partners in industry and government to bring the fruits of that research to society.

“We have capacity to do more, as many potential research partners in Australia and overseas are not necessarily aware of the breadth and depth of what we do,” he added. “If we are to have the greatest impact in the world at large, as a university and as engineers, we need to get our research out to the world.  And the creation of INGENUITY is part of that effort.”

Hoffman said the magazine was one of a number of initiatives UNSW Engineering is pursuing to enhance the Faculty’s global impact and its academic and research excellence.

“In May, we hosted the first Ingenuity Fellow, a journalist-in-residence program for overseas science journalists. Our inaugural recipient was Rebecca Morelle, global science correspondent for BBC News in London, and she spent three weeks on-campus meeting some of our best minds and most impressive innovators. And last month, we held a sold-out public event with Peter Norvig, Research Director at Google, talking about Google’s approach to artificial intelligence and machine learning.

“We mean to not just be the leading engineering faculty in the country but, in a global industry, to be seen as one of the great engineering faculties of the world,” he concluded.

Through engaging storytelling by some of the country’s finest science writers, stylish design and beautiful photography, INGENUITY will bring to life the Faculty’s work in areas like quantum computing, bionic vision, solar energy, water and city environments, artificial intelligence, biomedical instrumentation, robotics, advanced polymers, space research, materials and membranes, cyber security and sustainable design.

The free magazine is being distributed to senior executives of Australia’s largest corporations, federal and state parliamentarians and senior government officials, scientific and industry collaborators of UNSW’s Faculty of Engineering globally, as well as science and technology journalists worldwide. The print edition is also being distributed to Australian embassies and trade offices overseas, and at the biennial World Conference of Science Journalists and the Annual Meeting of the American Association for the Advancement of Science.

The magazine is produced by specialist custom publishing house Refraction Media, whose clients include Google, the CRC Association, the Office to the Chief Scientist and ANSTO, and who was named Best Small Publisher in 2015 at the annual Publish Awards.

“Quality long-form journalism in science and technology is hard to come by in Australia,” said Wilson da Silva, the faculty’s senior communications advisor and former editor-in-chief of COSMOS magazine, which he co-founded with Alan Finkel, now Australia’s Chief Scientist. “There’s a wealth of great research stories to tell at UNSW, and we hope that everyone, including the general public, will enjoy the quality writing in INGENUITY and the great stories of Australian research excellence it has to tell.”

How to receive INGENUITY:

This information was first shared by UNSW Engineering on 5 July 2017. 

digital disruption

Why digital disruption will create your next career

Like many of you I am waiting for digital disruption to make my job redundant so I can lean out, reclaim my work-life balance and let the robots do the rest.

As a journalist, my first thought was to see how digital disruption could work for me, so I looked for an artificial intelligence that could write this article for me (it couldn’t). But it came scarily close.

While so-called artificially intelligent chatbots are at best frustrating, programs such as Wordsmith can take sets of data and generate various articles based on simple coding of parameters, while stuffing a few synonyms in to sound like a genuine journalist.

Last week, an inaccurate post titled ‘The Trump Effect: It’s Happening Already!!’ went viral, and Facebook announced it would instigate third party fact checking to crack down on fake news. Imagine a world where AI could both check the accuracy of posts, but also one in which AI could generate endless streams of viral click bait.

Need a meeting? Download an artificial assistant like Amy from x.ai to contact your clients directly and discuss suitable times. All you do is turn up.

Fancy a bite to eat? Before long autonomous vehicles will be at your beck and call to escort you to your favourite restaurant or deliver a much-loved takeaway.

Work in a construction trade or manufacturing? Robotics and 3D printing can download, print and stack your bricks, scaffolds and planking, twist your toothpaste caps on and sort quality from flawed product.

What about a highly-paid, precision career such as surgery? Google is already working with Johnson and Johnson’s medical device company Ethicon on the next generation of surgical robots – research that is based on Google’s work in autonomous cars.

Chances are if you teach and/or work in academic research, you’ll already be aware of the possibilities of massive open online courses (MOOCs) and their potential for disrupting the way we learn, and allow access to our institutions. In four years, MOOCs have gone from zero to over 4,000 courses reaching around 35 million students.

Worried? You’re not alone, a PwC survey of CEO’s globally found 62% of 1300 surveyed were concerned about the impact of digital disruption in their industry. I recently heard a leader from the giant resources company BHP talking at the AFR Innovation Summit about being a recycler rather than a producer of steel after their disastrous 2015 downturn.

But if you think digital disruption means the robots are coming for your job, you’re wrong. While just under half of our jobs are expected to be at risk of automation in the next 10–15 years, for every disrupted career area, new opportunities arise. Like writing the programming software to create news stories or humanising the language used by AIs. By researching the signals that can make autonomous cars safer for pedestrians or by understanding the psychology behind creating incentives for innovation in your staff.

Where are we most at risk from missing the opportunities from digital disruption? Our team of thought leaders have the answers.

Heather Catchpole

Managing Director and Head of Content, Refraction Media

Read next: Head of KPMG Innovate, James Mabbott, uncovers the point of difference between those who remain resilient to change and those who get left behind.

Spread the word: Help Australia become digital savvy nation! Share this piece on digital disruptors using the social media buttons below.

More Thought Leaders: Click here to go back to the Thought Leadership Series homepage, or start reading the Women in STEM Thought Leadership Series here.


Chatting with chatbots

Human communication goes beyond words. It is complex, rich in nuances and frequently includes non-verbal signs. Yet despite our technological limitations it is not impossible for some aspects of communication to be emulated by a machine with surprising effect.

This has been part of the challenge in developing Harlie (Human and Robot Language Interaction Experiment), a smartphone chatbot app developed by researchers from the CSIRO’s e-health research program and the University of Queensland.

It’s primarily aimed at people who may have trouble conversing including those with neurological conditions such as Parkinson’s disease and dementia, or even autism.

The following dialog excerpt took place between a human who has autism, let’s call him Chris (pseudonym), and Harlie.

Harlie: Are you part of a community group?

Chris: Um, yes I am.

Harlie: I see. I hear that community groups often offer the opportunity to craft and build things. Is that something you enjoy doing?

Chris: Oh yes I do. This is really exciting.

Harlie: I see. What kind of things do you wish you could make one day?

Chris: Wooden train.

Harlie: That sounds like a great thing to aspire to. What project would recommended to a beginner like me?

Chris: Uh huh a bird feeder.

Harlie: Thanks. I will add that to my list. What supplies would I need to buy for my toolkit?

Chris: Ah hammer, nails, good supply of wood.

But Harlie, like all other artificial intelligent (AI) programs, has no concept of community groups, woodwork or anything else for that matter. That is to say it has no sentience.

And alas, sentient chatbots are seemingly light years beyond our reach. But is sentience needed to convey ideas, feelings and activities?

To some degree, no.

Chatbot programmers, or botmasters, develop and maintain a large repository of responses to the plethora of input statements that could be made by the user.

The way most modern chatbots operate is illustrated in this figure.

The typical chatbot brain is a tree-like structure. Credit: David Ireland

Phrases that could be uttered by a human are grouped together to form branches. At the end of the branch, is the leaf, or a piece of code that is executed by the machine.

This code could simply be “respond with ‘Hi human'” or it could be a machine learning algorithm determining the appropriate response based on current semantics and context.

This is where the exciting research is happening.

New branches are added continuously through conversations and feedback with potential customers, as is the case with Harlie, or through self-learning as was seen in the disastrous example of Microsoft’s social media chatbot Tay, which was shut down within a day of going live earlier this year after declaring, among other controversial tweets, that “Hitler was right”.

A more successful use of AI was revealed earlier this month in the USA. Students studying artificial intelligence at the Georgia Institute of Technology discovered that “Jill”, one of the teaching assistants responding to their emails regarding a course, was actually a computer powered by IBM’s Watson analytics system.

Jill’s responses were simply based on the answers to questions that previous students had asked about the course. As the college points out, students tend to ask the same questions over and over and after some initial tinkering, Jill was able to answer students with about 97% certainty.

The ELIZA effect

Attempts to create a convincing conversation with a machine have been going on for decades.

The first chatbot was called ELIZA. Developed in 1966, the program was created by Joseph Weizenbaum at MIT. This program was unparalleled because for the first time a machine could seemingly converse with a human.

ELIZA emulated a psychotherapist’s responses to would-be patients in replies generated for typed, text-only conversations.

By identifying key words and phrases, ELIZA was able to respond with surprising intelligibility and insight. In fact, it was so highly personified by some users that they would spend hours conversing and refused to share conversation records with researchers.

This phenomenon become known as the ELIZA effect. An excerpt of a famous ELIZA transcript that was published in 1966 between ELIZA and a young woman is given below.

Human: Well, my boyfriend made me come here.

ELIZA: Your boyfriend made you come here?

Human: He says I’m depressed much of the time.

ELIZA: I am sorry to hear you are depressed.

Human: It’s true. I am unhappy.

ELIZA: Do you think coming here will help you not to be unhappy?

Human: I need some help, that much seems certain.

ELIZA: What would it mean to you if you got some help?

Human: Perhaps I could learn to get along with my mother.

ELIZA: Tell me more about your family.

Modern day

Since ELIZA, computer power has increased at an exponential rate, but how far have we come towards a next generation of chatbots? Voice recognition is now an accepted part of smartphone technology with Google Now and Apple’s Siri. But what about developments in actual conversations with AI?

An annual AI competition is held where human judges speak to different chatbots whose developers are seeking the coveted Loebner prize and the deadline for entries this year is 1 July. The winner is decided by judges who determine the most human-like chatbot.

A prominent entry and winner in 2013 was the Mitsuku chatbot, which was designed for more general typed conversation.

The Mitsuku website provides a Turing test to gauge humans perceptions of the chatbot.

The human user is either connected to a real human or Mitsuku. Results show that on average, 12% of people thought they were talking to a human when in fact they were talking to a machine.

Here is a dialog excerpt from Mitsuku showing her apparent wit:

Human: What’s the difference between a man and a woman?

Mitsuku: A man – a male human being. A woman is a man built to more complete specifications.

Human: That’s not what I meant.

Mitsuku: Oh sorry, what do you mean?

Human: What does a man have a woman doesn’t?

Mitsuku: A well paid job?

Last year’s winner of the Loebner prize was called Rose and it is possible to have a spoken conversation with the chatbot on some web browsers. She too can be quite witty, and talkative too.

The future

Microsoft’s CEO, Satya Nadella said at an event in March that chatbots will have, “as profound an impact as previous shifts we’ve had”. Much like the shift that occurred with the introduction of the graphical user interface, the web browser or touchscreen.

But there are numerous challenges ahead and building a convincing chatbot requires enormous amounts of data and time.

Microsoft’s Tay showed us the dangers of using shortcuts by crowd-sourcing unchecked new branches into Tay’s brain.

In contrast, the Mitsuku developer has taken the long road and constantly refined Mitsuku’s digital brain since 2004.

Nevertheless, the possibility of Harlie helping users who struggle with communication, or of Mitsuku providing a convincing partner, suggests talking machines may go beyond current smartphone use in making hotel bookings and providing directions, and become something much more in the next generation.

– Dr David Ireland, Dr Christina Atay and Dr Jacki Liddle

This article was first published by The Conversation on 18 May 2016. Read the original article here.