We are all familiar with physical, industrial robots, but what about robots that work in offices? In fact, they are already taking up posts around the world alongside their human counterparts. What opportunities does the Virtual Workforce present, and why are organisations choosing them to facilitate better service, faster growth and to react more quickly to market opportunities? This talk examines the art of the possible and how a Virtual Workforce can increase both the job satisfaction of human workers and transform the way that enterprises and global service providers deliver value. David Moss is CTO and Co-founder of Blue Prism Limited, a UK tech company formed in 2001 to pursue the dream of delivering the vision of robotics into the oce environment. David is a technologist and thought leader in the Robotic Process Automation movement and a pioneer in the creation of the Virtual Workforce concept.
1) Robotic Process Automation is the next step in productivity enhancement brought about by technology. What is the key issue here about robots replacing humans?
2) Why has it taken (and continues to take) so long to get robots (automation) into the service industry whereas it has been around for decades (arguably since the late 1800s) in the industrial setting?
Xiaomi Corp., going for wow-factor ahead of what could be the largest initial public offering since 2014, has revealed a blistering pace of growth that’ll help it take on Apple and Samsung in global smartphones.
The Chinese smartphone maker filed for an IPO in Hong Kong Thursday, kicking off a process that’s expected to raise at least $10 billion and confer a value of $100 billion on the eight-year-old company. That offered investors a glimpse into the inner workings of the company controlled by billionaire Lei Jun, and its ups-and-downs since almost dropping off the radar in 2016.
In 2013 Carl Benedikt Frey and Michael A. Osborne of Oxford University published a report titled “The Future of Employment: How susceptible are jobs to computerisation?”. The authors examine how susceptible jobs are to computerisation, by implementing a novel methodology to estimate the probability of computerisation for 702 detailed occupations, using a Gaussian process classifier.
According to their estimates, about 47 percent of total US employment is at risk. Although the report is specific to the US job market, it is easy to see how this might apply all over the world.
We extracted the jobs and the probability of automation from the report and have made it easy to search for your job. We’ve added some additional information from the Bureau of Labor Statistics to provide some additional information about the jobs.
I used this website in class during a discussion on careers in MIS. What I did was pull up the website and then I talked about this being based on research from Oxford University. I then said that I would put something in to start us going. I entered “Truck Driver”. The website pulls up a list of jobs that match that description. Before clicking on one of those from the list, we had a short class discussion about what we thought the probability was for automation. So, for truck driver we had already covered that driverless vehicles have progressed so much that Google has already driven 4 million miles without a driver, and that Volvo has already delivered a truck load of Coors beer in a driverless truck, As such, class thought that “long haul truck drivers” had a pretty high chance of being replaced by robots. We settled on 75% chance. Then we clicked on “heavy and tractor-trailer truck drivers”, and the response from the website is that there is a 79% chance of them being replaced.
We repeated this with suggestions from class. Suggestions included Nurse (class thought low chance and the website says 0.9%), College Professor (we used computer and information research scientists, which class thought low chance and the website says 1.5%), pilot and so on.
Accountant comes out at 94%, which is a very interesting discussion for those in class who might want to study accounting.
Professional athlete comes out at 28%, which many thought way too high. I discussed how eSports is becoming huge, with professional teams and world wide competitions. The biggest athletes in South Korea are online race car drivers. With this knowledge, 28% might actually be low.
Society is on the verge of a new industrial revolution – upending business, commerce, culture and nearly every other aspect of human life. Driving this revolution is the fusion of digital technology with the physical and biological worlds. Disruption is now a way of life that we all need to get use to. Organizations like PwC are still learning how to harness artificial intelligence, robotics and other emerging technologies to best help our clients, our people, and society.
This whirlwind of new ideas offers unimagined opportunities and new threats, as organizations plan for an uncertain, tech-enabled future. While we don’t know exactly what this new world will look like, there is destined to be one constant: humans will be more crucial than ever in shaping, deploying and powering new technology.
Without the right people to guide it, investment in emerging technology is aimless and destined for failure. We need a talent pipeline that speaks the same language as the machines in their pockets.
If you’ve got an old laptop collecting dust in your home, you’re not alone. In a survey conducted last spring by the Consumer Reports Survey Group, a quarter of the members who had purchased multiple laptops since 2014 confessed to letting one of those devices linger under the roof—unused—after it had been replaced.
And that raises a good question: How do you go about finding a new home for an old laptop? With Earth Day approaching, here are a few eco-friendly options to consider.
MACHINE-LEARNING is beginning to shake up finance. A subset of artificial intelligence (AI) that excels at finding patterns and making predictions, it used to be the preserve of technology firms. The financial industry has jumped on the bandwagon. To cite just a few examples, “heads of machine-learning” can be found at PwC, a consultancy and auditing firm, at JP Morgan Chase, a large bank, and at Man GLG, a hedge-fund manager. From 2019, anyone seeking to become a “chartered financial analyst”, a sought-after distinction in the industry, will need AI expertise to pass his exams.
1) “JPMorgan Chase deployed software that can sift through 12,000 commercial-loan contracts in seconds, compared with the 360,000 hours it used to take lawyers and loan officers to review the contracts.” What impact will technology like this have on careers in finance and law?
2) What are you doing, independent of which major you are choosing, to become better at AI?
Eleanor Margolis had used PayPal for more than a decade when the online payment provider blocked her account in January. The reason: She was 16 years old when she signed up, and PayPal Holdings Inc. insists she should have known the minimum age is 18, because the rule is clearly stated in terms and conditions she agreed to. Clearly stated, that is, in a document longer than The Great Gatsby—almost 50,000 words spread across 21 separate web pages. “They didn’t have any checks in place to make sure I was over 18,” says Margolis, now 28. “Instead, they contact me 12 years later. It’s completely absurd.”
Source: Bloomberg Technology News
Date: April 20th, 2018
1) “In 2005 security-software provider PC Pitstop LLC promised a $1,000 prize to the first user to spot the offer deep in its terms and conditions; it took four months before the reward was claimed.” What might be better ways to make sure users know what they are signing up for?
2) What might be an appropriate length of terms and conditions that it would be sensible for a company to say that they are “clearly stated”? That is, how much should a reasonable user be expected to read and understand when signing up for an online app or service?