AT&T’s $1 billion gambit: Retraining nearly half its workforce for jobs of the future — from by Susan Caminiti

Excerpts (emphasis DSC):

  • AT&T initiated a massive retraining effort after discovering that nearly half of its 250,000 employees lacked the necessary skills needed to keep the company competitive.
  • Ninety percent of maturing companies expect digital disruption, but only 44 percent are adequately preparing for it.
  • Despite the federal government’s investment in job-retraining efforts, most are deemed ineffective.


The discovery presented AT&T with two daunting options, explains Bill Blase, senior executive vice president of human resources. “We could go out and try to hire all these software and engineering people and probably pay through the nose to get them, but even that wouldn’t have been adequate,” he explains. “Or we could try to reskill our existing workforce so they could be competent in the technology and the skills required to run the business going forward.”


In a world where technology advances are measured in months, not years, companies selling everything from computers and cellphones to cereal and sneakers are trying desperately to adapt. A recent research report by the Society for Human Resource Management states that nearly 40 percent of hiring managers cite lack of technical skills among the reasons why they can’t fill job openings.

And the message isn’t lost on workers, either. A 2016 Pew Research Center survey shows that more than half of the adults in the workforce today realize that it will be essential for them to get training and develop new skills throughout their career in order to keep up with changes in the workplace.

In fact, according to Willis Towers Watson, 90 percent of maturing companies expect digital disruption, but only 44 percent are adequately preparing for it — and getting the right people to get the work done remains a challenge for most.

AT&T’s massive global retraining program — the company prefers to call it “reskilling” — is perhaps corporate America’s boldest response to this war for talent. Known inside the company as Future Ready, the initiative is a $1 billion web-based, multiyear effort that includes online courses; collaborations with Coursera, Udacity and leading universities; and a career center that allows employees to identify and train for the kinds of jobs the company needs today and down the road. An online portal called Career Intelligence lets workers see what jobs are available, the skills required for each, the potential salary range and whether that particular area is projected to grow or shrink in the years ahead. In short, it gives them a roadmap to get from where they are today to where the company needs them to be in the future.



From DSC:
This article is encouraging in at least a couple of ways to me:

  • A large company is choosing to retrain its employees, helping them to learn and grow — to reinvent themselves and to stay relevant
  • A large company is recognizing the exponential pace of change that we’re now on. The question is, are we ready for it?




On Change and Relevance for Higher Education — from by Mary Grush and Phil Long
A Q&A with Phil Long


Mary Grush: You’ve been connected to scores of technology leaders and have watched trends in higher education for more than 30 years. What is the central, or most important concern you are hearing from institutional leadership now?

Phil Long: Higher ed institutions are facing some serious challenges to stay relevant in a world that is diversifying and changing rapidly. They want to make sure that the experiences they have designed for students will carry the next generation forward to be productive citizens and workers. But institutions’ abilities to keep up in our changing environment have begun to lag to a sufficient degree, such that alternatives to the traditional university are being considered, both by the institutions themselves and by their constituents and colleagues throughout the education sector.

Grush: What are a few of the more specific areas in which institutions may find it difficult to navigate?

Long: Just from a very high level view, I’d include on that list: big data and the increasing sophistication of algorithms, with the associated benefits and risks; artificial intelligence with all its implications for good… and for peril; and perhaps most importantly, new applications and practices that support how we recognize learning.



“The pace of change never seems to slow down. And the issues and implications of the technologies we use are actually getting broader and more profound every day.” — Phil Long




The Space Satellite Revolution Could Turn Earth into a Surveillance Nightmare — from by Becky Ferreira
Laser communication between satellites is revolutionizing our ability to track climate change, manage resources, and respond to natural disasters. But there are downsides to putting Earth under a giant microscope.


And while universal broadband has the potential to open up business and education opportunities to hundreds of thousands of people, it’s the real-time satellite feeds of earth that may have both the most immediate and widespread financial upsides — and the most frightening surveillance implications — for the average person here on earth.

Among the industries most likely to benefit from laser communications between these satellites are agriculture and forestry.

Satellite data can also be used to engage the public in humanitarian efforts. In the wake of Typhoon Haiyan, DigitalGlobe launched online crowdsourcing campaigns to map damage and help NGOs respond on the ground. And they’ve been identifying vulnerable communities in South Sudan as the nation suffers through unrest and famine.

In an age of intensifying natural disasters, combining these tactics with live satellite video feeds could mean the difference between life and death for thousands of people.

Should a company, for example, be able to use real-time video feeds to track your physical location, perhaps in order to better target advertising? Should they be able to use facial recognition and sentiment analysis algorithms to assess your reactions to those ads in real time?

While these commercially available images aren’t yet sharp enough to pick up intimate details like faces or phone screens, it’s foreseeable that regulations will be eased to accommodate even sharper images. That trend will continue to prompt privacy concerns, especially if a switch to laser-based satellite communication enables near real-time coverage at high resolutions.

A kaleidoscopic swirl of possible futures confronts us, filled with scenarios where law enforcement officials could rewind satellite footage to identify people at a crime scene, or on a more familial level, parents could remotely watch their kids — or keep tabs on each other — from space. In that world, it’s not hard to imagine privacy becoming even more of a commodity, with wealthy enclaves lobbying to be erased from visual satellite feeds, in a geospatial version of “gated communities.”



From DSC:
The pros and cons of technologies…hmmm…this article nicely captures the pluses and minuses that societies around the globe need to be aware of, struggle with, and discuss with each other. Some exciting things here, but some disturbing things here as well.




In Move Towards More Online Degrees, Coursera Introduces Its First Bachelor’s — from by Sydney Johnson


These days, though, many MOOC platforms are courting the traditional higher-ed market they once rebuked, often by hosting fully-online masters degrees for colleges and universities. And today, one of the largest MOOC providers, Coursera, announced it’s going one step further in that direction, with its first fully online bachelor’s degree.

“We are realizing that the vast reach of MOOCs makes them a powerful gateway to degrees,” Coursera CEO Jeff Maggioncalda said in a statement.

The new degree will be a bachelor of science in computer science from the University of London. The entire program will cost between £9,600 and £17,000 (approximately $13,300 to $23,500), depending on a student’s geographic location. According to a spokesperson for Coursera, the program’s “cost is adjusted based on whether a student is in a developed or developing economy.”



From DSC:
At least a couple of questions come to mind here:

  • What might the future hold if the U.S. Department of Education / the Federal Government begins funding these types of alternatives to traditional higher education?
  • Will Coursera be successful here and begin adding more degrees? If so, a major game-changer could be on our doorsteps.




Uber and Lyft drivers’ median hourly wage is just $3.37, report finds — from by Sam Levin
Majority of drivers make less than minimum wage and many end up losing money, according to study published by MIT

Excerpt (emphasis DSC):

Uber and Lyft drivers in the US make a median profit of $3.37 per hour before taxes, according to a new report that suggests a majority of ride-share workers make below minimum wage and that many actually lose money.

Researchers did an analysis of vehicle cost data and a survey of more than 1,100 drivers for the ride-hailing companies for the paper published by the Massachusetts Institute of Technology’s Center for Energy and Environmental Policy Research. The report – which factored in insurance, maintenance, repairs, fuel and other costs – found that 30% of drivers are losing money on the job and that 74% earn less than the minimum wage in their states.

The findings have raised fresh concerns about labor standards in the booming sharing economy as companies such as Uber and Lyft continue to face scrutiny over their treatment of drivers, who are classified as independent contractors and have few rights or protections.

“This business model is not currently sustainable,” said Stephen Zoepf, executive director of the Center for Automotive Research at Stanford University and co-author of the paper. “The companies are losing money. The businesses are being subsidized by [venture capital] money … And the drivers are essentially subsidizing it by working for very low wages.”



From DSC:
I don’t know enough about this to offer much feedback and/or insights on this sort of thing yet. But while it’s a bit too early for me to tell — and though I’m not myself a driver for Uber or Lyft — this article prompts me to put this type of thing on my radar.

That is, will the business models that arise from such a sharing economy only benefit a handful of owners or upper level managers or will such new business models benefit the majority of their employees? I’m very skeptical in these early stages though, as there aren’t likely medical or dental benefits, retirement contributions, etc. being offered to their employees with these types of companies. It likely depends upon the particular business model(s) and/or organization(s) being considered, but I think that it’s worth many of us watching this area.



Also see:

The Economics of Ride-Hailing: Driver Revenue, Expenses and Taxes— from / MIT Center for Energy and Environmental Policy Research by Stephen Zoepf, Stella Chen, Paa Adu, and Gonzalo Pozo

February 2018

We perform a detailed analysis of Uber and Lyft ride-hailing driver economics by pairing results from a survey of over 1100 drivers with detailed vehicle cost information. Results show that per hour worked, median profit from driving is $3.37/hour before taxes, and 74% of drivers earn less than the minimum wage in their state. 30% of drivers are actually losing money once vehicle expenses are included. On a per-mile basis, median gross driver revenue is $0.59/mile but vehicle operating expenses reduce real driver profit to a median of $0.29/mile. For tax purposes the $0.54/mile standard mileage deduction in 2016 means that nearly half of drivers can declare a loss on their taxes. If drivers are fully able to capitalize on these losses for tax purposes, 73.5% of an estimated U.S. market $4.8B in annual ride-hailing driver profit is untaxed.

Keywords: Transportation, Gig Economy, Cost-Bene t Analysis, Tax policy, Labor Center
Full Paper
| Research Brief



Addendum on 3/7/18:

The ride-hailing wage war continues

How much do Lyft and Uber drivers really make? After reporting in a study that their median take-home pay was just 3.37/hour—and then getting called out by Uber’s CEO—researchers have significantly revised their findings.

Closer to a living wage: Lead author Stephen Zoepf of Stanford University released a statement on Twitter saying that using two different methods to recalculate the hourly wage, they find a salary of either $8.55 or $10 per hour, after expenses. Zoepf’s team will be doing a larger revision of the paper over the next few weeks.

Still low-balling it?: Uber and Lyft are adamant that even the new numbers underestimate what drivers are actually paid. “While the revised results are not as inaccurate as the original findings, driver earnings are still understated,” says Lyft’s director of communications Adrian Durbin.

The truth is out there: Depending on who’s doing the math, estimates range from $8.55 (Zoepf, et al.) up to over $21 an hour (Uber). In other words, we’re nowhere near a consensus on how much drivers in the gig-economy make.



Personalized Learning Meets AI With Watson Classroom

Personalized Learning Meets AI With Watson Classroom — from by Erin Gohl

Excerpt (emphasis DSC):

Teaching is truly a Herculean challenge. Even the very best teachers can keep only so many of these insights in their heads and make only so many connections between expectations and circumstances. They can be aware of only a fraction of the research on best practices. They have only so much time to collaborate and communicate with the other adults in a particular student’s life to share information and insights. To be the best of themselves, teachers need to have access to a warehouse of information, a research assistant to mine best practices, note takers to gather and record information on each student, a statistician to gauge effective practices, and someone to collaborate with to distill the next best step with each student. In recent years, a plethora of vendors have developed software solutions that promise to simplify this process and give schools and teachers the answers to understand and address the individual needs of each student. One of the most promising, which I recently had a chance to learn about, is IBM’s Watson Classroom.

IBM is clear about what makes Watson different than existing solutions. First of all, it is a cognitive partner; not a solution. Secondly, it does not require proprietary or additional assessments, curriculum, or content. It uses whatever a district has in place. But it goes beyond the performance of tiering difficulty, pace, and reading level that is now standard fare for the solutions promising individualized, adaptive and personalized learning. Watson takes the stew of data from existing systems (including assessments, attendance records, available accommodations), adds the ability to infer meaning from written reports, and is able to connect the quality of the result to the approach that was taken. And then adjust the next recommendation based on what was learned. It is artificial intelligence (AI) brought to education that goes far beyond the adaptive learning technologies of today.

Watson Classroom is currently being piloted in 12 school districts across the country. In those classrooms, Watson Classroom is utilizing cutting-edge computing power to give teachers a full range of support to be the best versions of themselves. Watson is facilitating the kind of education the great teachers strive for every day–one where learning is truly personalized for each and every student. Bringing the power of big data to the interactions between students and teachers can help assure that every student reaches beyond our expectations to achieve their full potential.




Learn with Google AI: Making ML education available to everyone — from


To help everyone understand how AI can solve challenging problems, we’ve created a resource called Learn with Google AI. This site provides ways to learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems. From deep learning experts looking for advanced tutorials and materials on TensorFlow, to “curious cats” who want to take their first steps with AI, anyone looking for educational content from ML experts at Google can find it here.

Learn with Google AI also features a new, free course called Machine Learning Crash Course (MLCC). The course provides exercises, interactive visualizations, and instructional videos that anyone can use to learn and practice ML concepts.



7 Ways Chatbots and AI are Disrupting HR — from
Enterprises are embracing AI for automating human resources


Chatbots and AI have become household names and enterprises are taking notice. According to a recent Forrester survey, roughly “85% of customer interactions within an enterprise will be with software robots in five years’ time” and “87% of CEOs are looking to expand their AI workforce” using AI bots.

In an effort to drive increased labor efficiencies, reduce costs, and deliver better customer/employee experiences enterprises are quickly introducing AI, machine learning, and natural language understanding as core elements of their digital transformation strategy in 2018.

Human resources (HR) is one area ripe for intelligent automation within an enterprise. AI-powered bots for HR are able to streamline and personalize the HR process across seasonal, temporary, part-time, and full-time employees.

There are 7 ways in which enterprises can use HR bots to drive increased labors efficiencies, reduced costs, and better employee experiences:

  1. Recruitment
  2. Onboarding
  3. Company Policy FAQs
  4. Employee Training
  5. Common Questions
  6. Benefits Enrollment
  7. Annual Self-Assessment/Reviews


From DSC:
Again, this article paint a bit too rosy of a picture for me re: the use of AI and HR, especially in regards to recruiting employees.




Implementation of AI into eLearning. Interview with Christopher Pappas — from by Darya Tarliuk


Every day we hear more and more about the impact that Artificial Intelligence gains in every sphere of our life. In order to discover how AI implementation is going to change the eLearning we decided to ask Christopher Pappas to share his views and find out what he thinks about it. Christopher is an experienced eLearning specialist and the Founder of the eLearning Industry’s Network.

How to get ready preparing course materials now, while considering the future impact of AI?
Christopher: Regardless of whether you plan to adopt an AI system as soon as they’re available to the mass market or you opt to hold off (and let others work out the glitches), infrastructure is key. You can prepare your course materials now by developing course catalogs, microlearning online training repositories, and personalized online training paths that fall into the AI framework. For example, the AI system can easily recommend existing resources based on a learners’ assessment scores or job duties. All of the building blocks are in place, allowing the system to focus on content delivery and data analysis.




Can You Trust Intelligent Virtual Assistants? — from by Gary Audin
From malicious hackers to accidental voice recordings, data processed through virtual assistants may open you to security and privacy risks.


Did you know that with such digital assistants your voice data is sent to the cloud or another remote location for processing? Is it safe to talk in front of your TV remote? Are you putting your business data at risk of being compromised by asking Alexa to start your meeting?





Thanks, Robots! Now These Four Non-Tech Job Skills Are In Demand — from by Christian Madsbjerg
The more we rely on AI and machine learning, the more work we need social scientists and humanities experts to do.


Automation isn’t a simple struggle between people and technology, with the two sides competing for jobs. The more we rely on robots, artificial intelligence (AI), and machine learning, the clearer it’s become just how much we need social scientists and humanities experts–not the reverse.

These four skills in particular are all unique to us humans, and will arguably rise in value in the coming years, as more and more companies realize they need the best of both worlds to unleash the potential from both humans and machines.






The number of Americans working for themselves could triple by 2020 — from by Amy Wang

Excerpt (emphasis DSC):

Americans are as eager to work as ever. Just no longer for somebody else.

According to FreshBooks, a cloud-based accounting company that has conducted a study on self-employment for two years, the number of Americans working for themselves looks to triple—to 42 million people—by 2020.

The trend, gauged in a survey of more than 2,700 full-time US workers in traditional, independent, and small business roles about their career plans, is largely being driven by millennial workers. FreshBooks estimates that of the next 27 million independent workers, 42% will be millennials. The survey, conducted with Research Now, also finds that Americans who already work for themselves are suddenly very content to keep doing so, with 97% of independent workers (up 10% from 2016) reporting no desire to return to traditional work.



From DSC:
With the continued trend towards more freelancing and the growth of a more contingent workforce…have our students had enough practice in selling themselves and their businesses to be successful in this new, developing landscape?

We need to start offering more courses, advice, and opportunities for practicing these types of skills — and the sooner the better!  I’m serious. Our students will be far more successful with these types of skills under their belt. Conversely, they won’t be able to persuade others and sell themselves and their businesses without such skills.



Robo retail: The automated store of the future is heading closer to our doorsteps. — from’


The automated store of the future is heading closer to our doorsteps.

Self-checkout and online delivery services might soon be outmoded. Automated, cashier-less and mobile, doorstep-accessible shopping outlets are popping up globally—these offer not only a quick and seamless shopping experience, but also allow customers to handpick the items they are seeking.

Retail giant Amazon launched its Amazon Go store in Seattle in late January 2018. Amazon Go stocks everyday items, Whole Foods Market goods and Amazon-branded meal kits, but has no cashiers, no check-out lines and no barcode scanners. Shoppers enter by scanning an app, shop and leave—items purchased are automatically charged to their accounts. Dilip Kumar, vice president of technology for Amazon Go, suggests the concept is Amazon’s answer to solving “time poverty,” which he calls people’s “number one problem.”

This is just the tip of the iceberg. While Amazon Go currently only operates in Seattle, two other mobile concepts are hoping to reach a wider audience by physically bringing roving stores directly to the consumer. Robomart, based in the Bay Area, is a prototype tap-to-request grab-and-go food mart. Conventional grocery delivery services like those run by Amazon, FreshDirect or Instacart don’t let customers select products for themselves. If you’re particular about the ripeness of an avocado or conscious about bruises on tomatoes, being able to choose your own produce is essential. An autonomy-focused platform like Robomart puts consumers in the metaphorical driver’s seat, while still maintaining a high level of ease.




From DSC:
Speaking of cashiers, I had some comments regarding the future of cashiers towards the bottom of this posting here.  Another relevant posting is: “Tech companies should stop pretending AI won’t destroy jobs” + 6 other items re: AI, bots, algorithms, & more




From DSC:
My comments below are not meant to bash anyone at the Institute for the Future (which I really respect) nor at MIT Technology Review, in fact I recently posted an item from the latter organization that I thought was great. But l
ooking at the list below, I can’t help but think, “Oh…that should be no problem!  Geez that’s easy! ………NOT!”

As people lose their jobs to AI, robots, bots, algorithms, automation and the like — and try to reinvent themselves — many people won’t have the skills, interests, aptitudes, funding, background/prior knowledge, etc. to carve out their niches, to find out how to build teams that utilize robots and AI, and to make sense of complex systems. How many of us truly understand the world we’re living in these days? No one does.

Again, no problem on mastering these 5 peak performance zones. Easy peazy lemon squeezy. Geeez.  (Please hear the intense sarcasm dripping off my comments.)

How unrealistic can we get? It’s like saying, “Everyone can learn to code. No problem.”  That’s not true at all, especially given the current state of computer programming. Many (most?) people simply don’t think that way. That’s why programmers are always in demand and they are often highly paid. Why? Because most people don’t want to do it, can’t do it, or choose not to do it.

Please, let’s get realistic.


From the 2/22/18 e-newsletter from MIT Technology Review

The five skills you need for jobs of the future

The Palo Alto-based think tank Institute for the Future partnered with software company Cornerstone OnDemand to produce a report that identifies 15 skills that workers need to succeed in the workplace of tomorrow. They fall into five main buckets:

  1. Make yourself known through reputation management: Carve out your niche and brand across a variety of platforms to distinguish yourself from the crowd.
  2. Master human and machine collaboration: Know how to build teams that utilize robots and AI, as well as humans.
  3. Build your tribe: Personal networks and social connections will take you to the next level in a tech-focused world.
  4. Make sense of complex systems: The ability to be creative and connect the dots between different industries and organizations will be rewarded.
  5. Build resilience in extreme environments: Learn to thrive in more a risk prone society and build yourself new safety nets.



“To be fit for this future, you need to master five peak performance zones. These are the basics of future fitness for everyone. No matter what your own personal mission in life is, these are the workout zones that will get you ready to face whatever comes next.”





Tech companies should stop pretending AI won’t destroy jobs — from / MIT Technology Review by Kai-Fu Lee
No matter what anyone tells you, we’re not ready for the massive societal upheavals on the way.

Excerpt (emphasis DSC):

The rise of China as an AI superpower isn’t a big deal just for China. The competition between the US and China has sparked intense advances in AI that will be impossible to stop anywhere. The change will be massive, and not all of it good. Inequality will widen. As my Uber driver in Cambridge has already intuited, AI will displace a large number of jobs, which will cause social discontent. Consider the progress of Google DeepMind’s AlphaGo software, which beat the best human players of the board game Go in early 2016. It was subsequently bested by AlphaGo Zero, introduced in 2017, which learned by playing games against itself and within 40 days was superior to all the earlier versions. Now imagine those improvements transferring to areas like customer service, telemarketing, assembly lines, reception desks, truck driving, and other routine blue-collar and white-­collar work. It will soon be obvious that half of our job tasks can be done better at almost no cost by AI and robots. This will be the fastest transition humankind has experienced, and we’re not ready for it.

And finally, there are those who deny that AI has any downside at all—which is the position taken by many of the largest AI companies. It’s unfortunate that AI experts aren’t trying to solve the problem. What’s worse, and unbelievably selfish, is that they actually refuse to acknowledge the problem exists in the first place.

These changes are coming, and we need to tell the truth and the whole truth. We need to find the jobs that AI can’t do and train people to do them. We need to reinvent education. These will be the best of times and the worst of times. If we act rationally and quickly, we can bask in what’s best rather than wallow in what’s worst.


From DSC:
If a business has a choice between hiring a human being or having the job done by a piece of software and/or by a robot, which do you think they’ll go with? My guess? It’s all about the money — whichever/whomever will be less expensive will get the job.

However, that way of thinking may cause enormous social unrest if the software and robots leave human beings in the (job search) dust. Do we, as a society, win with this way of thinking? To me, it’s capitalism gone astray. We aren’t caring enough for our fellow members of the human race, people who have to put bread and butter on their tables. People who have to support their families. People who want to make solid contributions to society and/or to pursue their vocation/callings — to have/find purpose in their lives.


Others think we’ll be saved by a universal basic income. “Take the extra money made by AI and distribute it to the people who lost their jobs,” they say. “This additional income will help people find their new path, and replace other types of social welfare.” But UBI doesn’t address people’s loss of dignity or meet their need to feel useful. It’s just a convenient way for a beneficiary of the AI revolution to sit back and do nothing.



To Fight Fatal Infections, Hospitals May Turn to Algorithms — from by John McQuaid
Machine learning could speed up diagnoses and improve accuracy


The CDI algorithm—based on a form of artificial intelligence called machine learning—is at the leading edge of a technological wave starting to hit the U.S. health care industry. After years of experimentation, machine learning’s predictive powers are well-established, and it is poised to move from labs to broad real-world applications, said Zeeshan Syed, who directs Stanford University’s Clinical Inference and Algorithms Program.

“The implications of machine learning are profound,” Syed said. “Yet it also promises to be an unpredictable, disruptive force—likely to alter the way medical decisions are made and put some people out of work.



Lawyer-Bots Are Shaking Up Jobs — from by Erin Winick


Meticulous research, deep study of case law, and intricate argument-building—lawyers have used similar methods to ply their trade for hundreds of years. But they’d better watch out, because artificial intelligence is moving in on the field.

As of 2016, there were over 1,300,000 licensed lawyers and 200,000 paralegals in the U.S. Consultancy group McKinsey estimates that 22 percent of a lawyer’s job and 35 percent of a law clerk’s job can be automated, which means that while humanity won’t be completely overtaken, major businesses and career adjustments aren’t far off (see “Is Technology About to Decimate White-Collar Work?”). In some cases, they’re already here.


“If I was the parent of a law student, I would be concerned a bit,” says Todd Solomon, a partner at the law firm McDermott Will & Emery, based in Chicago. “There are fewer opportunities for young lawyers to get trained, and that’s the case outside of AI already. But if you add AI onto that, there are ways that is advancement, and there are ways it is hurting us as well.”


So far, AI-powered document discovery tools have had the biggest impact on the field. By training on millions of existing documents, case files, and legal briefs, a machine-learning algorithm can learn to flag the appropriate sources a lawyer needs to craft a case, often more successfully than humans. For example, JPMorgan announced earlier this year that it is using software called Contract Intelligence, or COIN, which can in seconds perform document review tasks that took legal aides 360,000 hours.

People fresh out of law school won’t be spared the impact of automation either. Document-based grunt work is typically a key training ground for first-year associate lawyers, and AI-based products are already stepping in. CaseMine, a legal technology company based in India, builds on document discovery software with what it calls its “virtual associate,” CaseIQ. The system takes an uploaded brief and suggests changes to make it more authoritative, while providing additional documents that can strengthen a lawyer’s arguments.



Lessons From Artificial Intelligence Pioneers — from by Christy Pettey

CIOs are struggling to accelerate deployment of artificial intelligence (AI). A recent Gartner survey of global CIOs found that only 4% of respondents had deployed AI. However, the survey also found that one-fifth of the CIOs are already piloting or planning to pilot AI in the short term.

Such ambition puts these leaders in a challenging position. AI efforts are already stressing staff, skills, and the readiness of in-house and third-party AI products and services. Without effective strategic plans for AI, organizations risk wasting money, falling short in performance and falling behind their business rivals.

Pursue small-scale plans likely to deliver small-scale payoffs that will offer lessons for larger implementations

“AI is just starting to become useful to organizations but many will find that AI faces the usual obstacles to progress of any unproven and unfamiliar technology,” says Whit Andrews, vice president and distinguished analyst at Gartner. “However, early AI projects offer valuable lessons and perspectives for enterprise architecture and technology innovation leaders embarking on pilots and more formal AI efforts.”

So what lessons can we learn from these early AI pioneers?



Why Artificial Intelligence Researchers Should Be More Paranoid — from by Tom Simonite


What to do about that? The report’s main recommendation is that people and companies developing AI technology discuss safety and security more actively and openly—including with policymakers. It also asks AI researchers to adopt a more paranoid mindset and consider how enemies or attackers might repurpose their technologies before releasing them.



How to Prepare College Graduates for an AI World — from by
Northeastern University President Joseph Aoun says schools need to change their focus, quickly


WSJ: What about adults who are already in the workforce?

DR. AOUN: Society has to provide ways, and higher education has to provide ways, for people to re-educate themselves, reskill themselves or upskill themselves.

That is the part that I see that higher education has not embraced. That’s where there is an enormous opportunity. We look at lifelong learning in higher education as an ancillary operation, as a second-class operation in many cases. We dabble with it, we try to make money out of it, but we don’t embrace it as part of our core mission.



Inside Amazon’s Artificial Intelligence Flywheel — from by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.


Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.





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