5 questions we should be asking about automation and jobs — from hbr.org by Jed Kolko

Excerpts:

  1. Will workers whose jobs are automated be able to transition to new jobs?*
  2. Who will bear the burden of automation?
  3. How will automation affect the supply of labor?
  4. How will automation affect wages, and how will wages affect automation?
  5. How will automation change job searching?

 

From DSC:
For those Economics profs and students out there, I’m posted this with you in mind; also highly applicable and relevant to MBA programs.

* I would add a few follow-up questions to question #1 above:

  • To which jobs should they transition to?
  • Who can help identify the jobs that might be safe for 5-10 years?
  • If you have a family to feed, how are you going to be able to reinvent yourself quickly and as efficiently/flexibly as possible? (Yes…constant, online-based learning comes to my mind as well, as campus-based education is great, but very time-consuming.)

 

Also see:

We Still Don’t Know Much About the Jobs the AI Economy Will Make — or Take — from medium.com by Rachel Metz with MIT Technology Review
Experts think companies need to invest in workers the way they do for other core aspects of their business they’re looking to future-proof

One big problem that could have lasting effects, she thinks, is a mismatch between the skills companies need in new employees and those that employees have or know that they can readily acquire. To fix this, she said, companies need to start investing in their workers the way they do their supply chains.

 

Per LinkedIn:

Putting robots to work is becoming more and more popularparticularly in Europe. According to the European Bank for Reconstruction and Development, Slovakian workers face a 62% median probability that their job will be automated “in the near future.” Workers in Eastern Europe face the biggest likelihood of having their jobs overtaken by machines, with the textile, agriculture and manufacturing industries seen as the most vulnerable. • Here’s what people are saying.

 

Robot Ready: Human+ Skills for the Future of Work — from economicmodeling.com

Key Findings

In Robot-Ready, we examine several striking insights:

1. Human skills—like leadership, communication, and problem solving—are among the most in-demand skills in the labor market.

2. Human skills are applied differently across career fields. To be effective, liberal arts grads must adapt their skills to the job at hand.

3. Liberal art grads should add technical skills. There is considerable demand for workers who complement their human skills with basic technical skills like data analysis and digital fluency.

4. Human+ skills are at work in a variety of fields. Human skills help liberal arts grads thrive in many career areas, including marketing, public relations, technology, and sales.

 

 

 

5 things you will see in the future “smart city” — from interestingengineering.com by Taylor Donovan Barnett
The Smart City is on the horizon and here are some of the crucial technologies part of it.

5 Things You Will See in the Future of the Smart City

Excerpt:

A New Framework: The Smart City
So, what exactly is a smart city? A smart city is an urban center that hosts a wide range of digital technology across its ecosystem. However, smart cities go far beyond just this definition.

Smart cities use technology to better population’s living experiences, operating as one big data-driven ecosystem.

The smart city uses that data from the people, vehicles, buildings etc. to not only improve citizens lives but also minimize the environmental impact of the city itself, constantly communicating with itself to maximize efficiency.

So what are some of the crucial components of the future smart city? Here is what you should know.

 

 

 

Combining retrieval, spacing, and feedback boosts STEM learning — from retrievalpractice.org

Punchline:
Scientists demonstrated that when college students used a quizzing program that combined retrieval practice, spacing, and feedback, exam performance increased by nearly a letter grade.

—-

Abstract
The most effective educational interventions often face significant barriers to widespread implementation because they are highly specific, resource intense, and/or comprehensive. We argue for an alternative approach to improving education: leveraging technology and cognitive science to develop interventions that generalize, scale, and can be easily implemented within any curriculum. In a classroom experiment, we investigated whether three simple, but powerful principles from cognitive science could be combined to improve learning. Although implementation of these principles only required a few small changes to standard practice in a college engineering course, it significantly increased student performance on exams. Our findings highlight the potential for developing inexpensive, yet effective educational interventions that can be implemented worldwide.

In summary, the combination of spaced retrieval practice and required feedback viewing had a powerful effect on student learning of complex engineering material. Of course, the principles from cognitive science could have been applied without the use of technology. However, our belief is that advances in technology and ideas from machine learning have the potential to exponentially increase the effectiveness and impact of these principles. Automation is an important benefit, but technology also can provide a personalized learning experience for a rapidly growing, diverse body of students who have different knowledge and academic backgrounds. Through the use of data mining, algorithms, and experimentation, technology can help us understand how best to implement these principles for individual learners while also producing new discoveries about how people learn. Finally, technology facilitates access. Even if an intervention has a small effect size, it can still have a substantial impact if broadly implemented. For example, aspirin has a small effect on preventing heart attacks and strokes when taken regularly, but its impact is large because it is cheap and widely available. The synergy of cognitive science, machine learning, and technology has the potential to produce inexpensive, but powerful learning tools that generalize, scale, and can be easily implemented worldwide.

Keywords: Education. Technology. Retrieval practice. Spacing. Feedback. Transfer of learning.

 

 

An open letter to Microsoft and Google’s Partnership on AI — from wired.com by Gerd Leonhard
In a world where machines may have an IQ of 50,000, what will happen to the values and ethics that underpin privacy and free will?

Excerpt:

This open letter is my modest contribution to the unfolding of this new partnership. Data is the new oil – which now makes your companies the most powerful entities on the globe, way beyond oil companies and banks. The rise of ‘AI everywhere’ is certain to only accelerate this trend. Yet unlike the giants of the fossil-fuel era, there is little oversight on what exactly you can and will do with this new data-oil, and what rules you’ll need to follow once you have built that AI-in-the-sky. There appears to be very little public stewardship, while accepting responsibility for the consequences of your inventions is rather slow in surfacing.

 

In a world where machines may have an IQ of 50,000 and the Internet of Things may encompass 500 billion devices, what will happen with those important social contracts, values and ethics that underpin crucial issues such as privacy, anonymity and free will?

 

 

My book identifies what I call the “Megashifts”. They are changing society at warp speed, and your organisations are in the eye of the storm: digitization, mobilisation and screenification, automation, intelligisation, disintermediation, virtualisation and robotisation, to name the most prominent. Megashifts are not simply trends or paradigm shifts, they are complete game changers transforming multiple domains simultaneously.

 

 

If the question is no longer about if technology can do something, but why…who decides this?

Gerd Leonhard

 

 

From DSC:
Though this letter was written 2 years ago back in October of 2016, the messages, reflections, and questions that Gerd puts on the table are very much still relevant today.  The leaders of these powerful companies have enormous power — power to do good, or to do evil. Power to help or power to hurt. Power to be a positive force for societies throughout the globe and to help create dreams, or power to create dystopian societies while developing a future filled with nightmares. The state of the human heart is extremely key here — though many will hate me saying that. But it’s true. At the end of the day, we need to very much care about — and be extremely aware of — the characters and values of the leaders of these powerful companies. 

 

 

Also relevant/see:

Spray-on antennas will revolutionize the Internet of Things — from networkworld.com by Patrick Nelson
Researchers at Drexel University have developed a method to spray on antennas that outperform traditional metal antennas, opening the door to faster and easier IoT deployments.

 From DSC:
Again, it’s not too hard to imagine in this arena that technologies can be used for good or for ill.

 

 
 

10 jobs that are safe in an AI world — from linkedin.com by Kai-Fu Lee

Excerpts:

Teaching
AI will be a great tool for teachers and educational institutions, as it will help educators figure out how to personalize curriculum based on each student’s competence, progress, aptitude, and temperament. However, teaching will still need to be oriented around helping students figure out their interests, teaching students to learn independently, and providing one-on-one mentorship. These are tasks that can only be done by a human teacher. As such, there will still be a great need for human educators in the future.

Criminal defense law
Top lawyers will have nothing to worry about when it comes to job displacement. reasoning across domains, winning the trust of clients, applying years of experience in the courtroom, and having the ability to persuade a jury are all examples of the cognitive complexities, strategies, and modes of human interaction that are beyond the capabilities of AI. However, a lot of paralegal and preparatory work like document review, analysis, creating contracts, handling small cases, packing cases, and coming up with recommendations can be done much better and more efficiently with AI. The costs of law make it worthwhile for AI companies to go after AI paralegals and AI junior lawyers, but not top lawyers.

 

From DSC:
In terms of teaching, I agree that while #AI will help personalize learning, there will still be a great need for human teachers, professors, and trainers. I also agree w/ my boss (and with some of the author’s viewpoints here, but not all) that many kinds of legal work will still need the human touch & thought processes. I diverge from his thinking in terms of scope — the need for human lawyers will go far beyond just lawyers involved in crim law.

 

Also see:

15 business applications for artificial intelligence and machine learning — from forbes.com

Excerpt:

Fifteen members of Forbes Technology Council discuss some of the latest applications they’ve found for AI/ML at their companies. Here’s what they had to say…

 

 

 

How AI could help solve some of society’s toughest problems — from technologyreview.com by Charlotte Jee
Machine learning and game theory help Carnegie Mellon assistant professor Fei Fang predict attacks and protect people.

Excerpt:

Fei Fang has saved lives. But she isn’t a lifeguard, medical doctor, or superhero. She’s an assistant professor at Carnegie Mellon University, specializing in artificial intelligence for societal challenges.

At MIT Technology Review’s EmTech conference on Wednesday, Fang outlined recent work across academia that applies AI to protect critical national infrastructure, reduce homelessness, and even prevent suicides.

 

 

How AI can be a force for good — from science.sciencemag.org by Mariarosaria Taddeo & Luciano Floridi

Excerpts:

Invisibility and Influence
AI supports services, platforms, and devices that are ubiquitous and used on a daily basis. In 2017, the International Federation of Robotics suggested that by 2020, more than 1.7 million new AI-powered robots will be installed in factories worldwide. In the same year, the company Juniper Networks issued a report estimating that, by 2022, 55% of households worldwide will have a voice assistant, like Amazon Alexa.

As it matures and disseminates, AI blends into our lives, experiences, and environments and becomes an invisible facilitator that mediates our interactions in a convenient, barely noticeable way. While creating new opportunities, this invisible integration of AI into our environments poses further ethical issues. Some are domain-dependent. For example, trust and transparency are crucial when embedding AI solutions in homes, schools, or hospitals, whereas equality, fairness, and the protection of creativity and rights of employees are essential in the integration of AI in the workplace. But the integration of AI also poses another fundamental risk: the erosion of human self-determination due to the invisibility and influencing power of AI.

To deal with the risks posed by AI, it is imperative to identify the right set of fundamental ethical principles to inform the design, regulation, and use of AI and leverage it to benefit as well as respect individuals and societies. It is not an easy task, as ethical principles may vary depending on cultural contexts and the domain of analysis. This is a problem that the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems tackles with the aim of advancing public debate on the values and principles that should underpin ethical uses of AI.

 

 

Who’s to blame when a machine botches your surgery? — from qz.com by Robert Hart

Excerpt:

That’s all great, but even if an AI is amazing, it will still fail sometimes. When the mistake is caused by a machine or an algorithm instead of a human, who is to blame?

This is not an abstract discussion. Defining both ethical and legal responsibility in the world of medical care is vital for building patients’ trust in the profession and its standards. It’s also essential in determining how to compensate individuals who fall victim to medical errors, and ensuring high-quality care. “Liability is supposed to discourage people from doing things they shouldn’t do,” says Michael Froomkin, a law professor at the University of Miami.

 

 

Google Cloud’s new AI chief is on a task force for AI military uses and believes we could monitor ‘pretty much the whole world’ with drones — from businessinsider.in by Greg Sandoval

Excerpt:

“We could afford if we wanted to, and if we needed, to be surveilling pretty much the whole word with autonomous drones of various kinds,” Moore said. “I’m not saying we’d want to do that, but there’s not a technology gap there where I think it’s actually too difficult to do. This is now practical.”

Google’s decision to hire Moore was greeted with displeasure by at least one former Googler who objected to Project Maven.

“It’s worrisome to note after the widespread internal dissent against Maven that Google would hire Andrew Moore,” said one former Google employee. “Googlers want less alignment with the military-industrial complex, not more. This hire is like a punch in the face to the over 4,000 Googlers who signed the Cancel Maven letter.”

 

 

Organizations Are Gearing Up for More Ethical and Responsible Use of Artificial Intelligence, Finds Study — from businesswire.com
Ninety-two percent of AI leaders train their technologists in ethics; 74 percent evaluate AI outcomes weekly, says report from SAS, Accenture Applied Intelligence, Intel, and Forbes Insights

Excerpt:

AI oversight is not optional

Despite popular messages suggesting AI operates independently of human intervention, the research shows that AI leaders recognize that oversight is not optional for these technologies. Nearly three-quarters (74 percent) of AI leaders reported careful oversight with at least weekly review or evaluation of outcomes (less successful AI adopters: 33 percent). Additionally, 43 percent of AI leaders shared that their organization has a process for augmenting or overriding results deemed questionable during review (less successful AI adopters: 28 percent).

 

 

 

Do robots have rights? Here’s what 10 people and 1 robot have to say — from createdigital.org.au
When it comes to the future of technology, nothing is straightforward, and that includes the array of ethical issues that engineers encounter through their work with robots and AI.

 

 

 

To higher ed: When the race track is going 180mph, you can’t walk or jog onto the track. [Christian]

From DSC:
When the race track is going 180mph, you can’t walk or jog onto the track.  What do I mean by that? 

Consider this quote from an article that Jeanne Meister wrote out at Forbes entitled, “The Future of Work: Three New HR Roles in the Age of Artificial Intelligence:”*

This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.

Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more. 

 

From Robert Half’s 2019 Technology Salary Guide 

 

 

How many of us have those kinds of skills? Did we get that training in the community colleges, colleges, and universities that we went to? Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace. 

This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.

This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies. 

 

 

The below graphic is from:
Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages

 

 

 


 

* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:

  1. IBM: Vice President, Data, AI & Offering Strategy, HR
  2. Kraft Heinz Senior Vice President Global HR, Performance and IT
  3. SunTrust Senior Vice President Employee Wellbeing & Benefits

What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.

 


 

An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy 

Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.

 


 

 

How AI could help solve some of society’s toughest problems — from MIT Tech Review by Charlotte Jee
Machine learning and game theory help Carnegie Mellon assistant professor Fei Fang predict attacks and protect people.

Excerpt:

At MIT Technology Review’s EmTech conference, Fang outlined recent work across academia that applies AI to protect critical national infrastructure, reduce homelessness, and even prevent suicides.

 

 

Google Cloud’s new AI chief is on a task force for AI military uses and believes we could monitor ‘pretty much the whole world’ with drones — from businessinsider.in by Greg Sandoval

  • Andrew Moore, the new chief of Google Cloud AI, co-chairs a task force on AI and national security with deep defense sector ties.
  • Moore leads the task force with Robert Work, the man who reportedly helped to create Project Maven.
  • Moore has given various talks about the role of AI and defense, once noting that it was now possible to deploy drones capable of surveilling “pretty much the whole world.”
  • One former Googler told Business Insider that the hiring of Moore is a “punch in the face” to those employees.

 

 

How AI can be a force for good — from science.sciencemag.org

Excerpt:

The AI revolution is equally significant, and humanity must not make the same mistake again. It is imperative to address new questions about the nature of post-AI societies and the values that should underpin the design, regulation, and use of AI in these societies. This is why initiatives like the abovementioned AI4People and IEEE projects, the European Union (EU) strategy for AI, the EU Declaration of Cooperation on Artificial Intelligence, and the Partnership on Artificial Intelligence to Benefit People and Society are so important (see the supplementary materials for suggested further reading). A coordinated effort by civil society, politics, business, and academia will help to identify and pursue the best strategies to make AI a force for good and unlock its potential to foster human flourishing while respecting human dignity.

 

 

Ethical regulation of the design and use of AI is a complex but necessary task. The alternative may lead to devaluation of individual rights and social values, rejection of AI-based innovation, and ultimately a missed opportunity to use AI to improve individual wellbeing and social welfare.

 

 

Robot wars — from ethicaljournalismnetwork.org by James Ball
How artificial intelligence will define the future of news

Excerpt:

There are two paths ahead in the future of journalism, and both of them are shaped by artificial intelligence.

The first is a future in which newsrooms and their reporters are robust: Thanks to the use of artificial intelligence, high-quality reporting has been enhanced. Not only do AI scripts manage the writing of simple day-to-day articles such as companies’ quarterly earnings updates, they also monitor and track masses of data for outliers, flagging these to human reporters to investigate.

Beyond business journalism, comprehensive sports stats AIs keep key figures in the hands of sports journalists, letting them focus on the games and the stories around them. The automated future has worked.

The alternative is very different. In this world, AI reporters have replaced their human counterparts and left accountability journalism hollowed out. Facing financial pressure, news organizations embraced AI to handle much of their day-to-day reporting, first for their financial and sports sections, then bringing in more advanced scripts capable of reshaping wire copy to suit their outlet’s political agenda. A few banner hires remain, but there is virtually no career path for those who would hope to replace them ? and stories that can’t be tackled by AI are generally missed.

 

 

Who’s to blame when a machine botches your surgery? — from qz.com by Robert Hart

Excerpt:

That’s all great, but even if an AI is amazing, it will still fail sometimes. When the mistake is caused by a machine or an algorithm instead of a human, who is to blame?

This is not an abstract discussion. Defining both ethical and legal responsibility in the world of medical care is vital for building patients’ trust in the profession and its standards. It’s also essential in determining how to compensate individuals who fall victim to medical errors, and ensuring high-quality care. “Liability is supposed to discourage people from doing things they shouldn’t do,” says Michael Froomkin, a law professor at the University of Miami.

 

 

Alibaba looks to arm hotels, cities with its AI technology — from zdnet.com by Eileen Yu
Chinese internet giant is touting the use of artificial intelligence technology to arm drivers with real-time data on road conditions as well as robots in the hospitality sector, where they can deliver meals and laundry to guests.

Excerpt:

Alibaba A.I. Labs’ general manager Chen Lijuan said the new robots aimed to “bridge the gap” between guest needs and their expected response time. Describing the robot as the next evolution towards smart hotels, Chen said it tapped AI technology to address painpoints in the hospitality sector, such as improving service efficiencies.

Alibaba is hoping the robot can ease hotels’ dependence on human labour by fulfilling a range of tasks, including delivering meals and taking the laundry to guests.

 

 

Accenture Introduces Ella and Ethan, AI Bots to Improve a Patient’s Health and Care Using the Accenture Intelligent Patient Platform — from marketwatch.com

Excerpt:

Accenture has enhanced the Accenture Intelligent Patient Platform with the addition of Ella and Ethan, two interactive virtual-assistant bots that use artificial intelligence (AI) to constantly learn and make intelligent recommendations for interactions between life sciences companies, patients, health care providers (HCPs) and caregivers. Designed to help improve a patient’s health and overall experience, the bots are part of Accenture’s Salesforce Fullforce Solutions powered by Salesforce Health Cloud and Einstein AI, as well as Amazon’s Alexa.

 

 

German firm’s 7 commandments for ethical AI — from france24.com

Excerpt:

FRANKFURT AM MAIN (AFP) –
German business software giant SAP published Tuesday an ethics code to govern its research into artificial intelligence (AI), aiming to prevent the technology infringing on people’s rights, displacing workers or inheriting biases from its human designers.

 

 

 

 

The future of drug discovery and AI – the role of man and machine — from techemergence.com by  Ayn de Jesus

Excerpt:

Episode Summary: This week on AI in Industry, we speak with Amir Saffari, Senior Vice President of AI at BenevolentAI, a London-based pharmaceutical company that uses machine learning to find new uses for existing drugs and new treatments for diseases.

In speaking with him, we aim to learn two things:

  • How will machine learning play a role in the phases of drug discovery, from generating hypotheses to clinical trials?
  • In the future, what are the roles of man and machine in drug discovery? What processes will machines automate and potentially do better than humans in this field?

 

A few other articles caught my eye as well:

  • This little robot swims through pipes and finds out if they’re leaking — from fastcompany.com by Adele Peters
    Lighthouse, U.S. winner of the James Dyson Award, looks like a badminton birdie and detects the suction of water leaving pipes–which is a lot of water that we could put to better use.
    .
  • Samsung’s New York AI center will focus on robotics — from engadget.com by Saqib Shah
    NYU’s AI Now Institute is close-by and Samsung is keen for academic input.
    Excerpt:
    Samsung now has an artificial intelligence center in New York City — its third in North America and sixth in total — with an eye on robotics; a first for the company. It opened in Chelsea, Manhattan on Friday, walking distance from NYU (home to its own AI lab) boosting Samsung’s hopes for an academic collaboration.
    .
  • Business schools bridge the artificial intelligence skills gap — from swisscognitive.ch
    Excerpt:
    Business schools such as Kellogg, Insead and MIT Sloan have introduced courses on AI over the past two years, but Smith is the first to offer a full programme where students delve deep into machine learning.

    “Technologists can tell you all about the technology but usually not what kind of business problems it can solve,” Carlsson says. With business leaders, he adds, it is the other way round — they have plenty of ideas about how to improve their company but little way of knowing what the new technology can achieve. “The foundational skills businesses need to hack the potential of AI is the understanding of what problems the tech is actually good at solving,” he says.

 

 

 

Activists urge killer robot ban ‘before it is too late’ — from techxplore.com by Nina Larson

Excerpt:

Countries should quickly agree a treaty banning the use of so-called killer robots “before it is too late”, activists said Monday as talks on the issue resumed at the UN.

They say time is running out before weapons are deployed that use lethal force without a human making the final kill-order and have criticised the UN body hosting the talks—the Convention of Certain Conventional Weapons (CCW)—for moving too slowly.

“Killer robots are no longer the stuff of science fiction,” Rasha Abdul Rahim, Amnesty International’s advisor on artificial intelligence and human rights, said in a statement.

“From artificially intelligent drones to automated guns that can choose their own targets, technological advances in weaponry are far outpacing international law,” she said.

 

Activists urge killer robot ban before it is too late

 

From DSC:
I’ve often considered how much out front many technologies are in our world today. It takes the rest of society some time to catch up with emerging technologies and ask whether we should be implementing technology A, B, or C.  Just because we can, doesn’t mean we should. A worn-out statement perhaps, but given the exponential pace of technological change, one that is highly relevant to our world today.

 

 



Addendum on 9/8/18:



 

 

25 skills LinkedIn says are most likely to get you hired in 2018 — and the online courses to get them — from businessinsider.com by Mara Leighton

Excerpt:

With the introduction of far-reaching and robust technology, the job market has experienced its own exponential growth, adaptation, and semi-metamorphosis. So much so that it can be difficult to guess what skills employer’s are looking for and what makes your résumé — and not another — stand out to recruiters.

Thankfully, LinkedIn created a 2018 “roadmap”— a list of hard and soft skills that companies need the most.

LinkedIn used data from their 500+ million members to identify the skills companies are currently working the hardest to fill. They grouped the skills members add to their profiles into several dozen categories (for example, “Android” and “iOS” into the “Mobile Development” category). Then, the company looked at all of the hiring and recruiting activity that happened on LinkedIn between January 1 and September 1 (billions of data points) and extrapolated the skill categories that belonged to members who were “more likely to start a new role within a company and receive interest from companies.”

LinkedIn then coupled those specific skills with related jobs and their average US salaries — all of which you can find below, alongside courses you can take (for free or for much less than the cost of a degree) to support claims of aptitude and stay ahead of the curve.

The online-learning options we included — LinkedIn Learning, Udemy, Coursera, and edX— are among the most popular and inexpensive.

 

 

Also see:

 

 

 

State of AI — from stateof.ai

Excerpt:

In this report, we set out to capture a snapshot of the exponential progress in AI with a focus on developments in the past 12 months. Consider this report as a compilation of the most interesting things we’ve seen that seeks to trigger informed conversation about the state of AI and its implication for the future.

We consider the following key dimensions in our report:

  • Research: Technology breakthroughs and their capabilities.
  • Talent: Supply, demand and concentration of talent working in the field.
  • Industry: Large platforms, financings and areas of application for AI-driven innovation today and tomorrow.
  • Politics: Public opinion of AI, economic implications and the emerging geopolitics of AI.

 

definitions of terms involved in AI

definitions of terms involved in AI

 

hard to say how AI is impacting jobs yet -- but here are 2 perspectives

 

 

There’s nothing artificial about how AI is changing the workplace — from forbes.com by Eric Yuan

Excerpt:

As I write this, AI has already begun to make video meetings even better. You no longer have to spend time entering codes or clicking buttons to launch a meeting. Instead, with voice-based AI, video conference users can start, join or end a meeting by simply speaking a command (think about how you interact with Alexa).

Voice-to-text transcription, another artificial intelligence feature offered by Otter Voice Meeting Notes (from AISense, a Zoom partner), Voicefox and others, can take notes during video meetings, leaving you and your team free to concentrate on what’s being said or shown. AI-based voice-to-text transcription can identify each speaker in the meeting and save you time by letting you skim the transcript, search and analyze it for certain meeting segments or words, then jump to those mentions in the script. Over 65% of respondents from the Zoom survey said they think AI will save them at least one hour a week of busy work, with many claiming it will save them one to five hours a week.

 

 

 

AI can now ‘listen’ to machines to tell if they’re breaking down — from by Rebecca Campbell

Excerpt:

Sound is everywhere, even when you can’t hear it.

It is this noiseless sound, though, that says a lot about how machines function.

Helsinki-based Noiseless Acoustics and Amsterdam-based OneWatt are relying on artificial intelligence (AI) to better understand the sound patterns of troubled machines. Through AI they are enabling faster and easier problem detection.

 

Making sound visible even when it can’t be heard. With the aid of non-invasive sensors, machine learning algorithms, and predictive maintenance solutions, failing components can be recognized at an early stage before they become a major issue.

 

 

 

Chinese university uses facial recognition for campus entry — from cr80news.com by Andrew Hudson

Excerpt:

A number of higher education institutions in China have deployed biometric solutions for access and payments in recent months, and adding to the list is Peking University. The university has now installed facial recognition readers at perimeter access gates to control access to its Beijing campus.

As reported by the South China Morning Post, anyone attempting to enter through the southwestern gate of the university will no longer have to provide a student ID card. Starting this month, students will present their faces to a camera as part of a trial run of the system ahead of full-scale deployment.

From DSC:
I’m not sure I like this one at all — and the direction that this is going in. 

 

 

 

Will We Use Big Data to Solve Big Problems? Why Emerging Technology is at a Crossroads — from blog.hubspot.com by Justin Lee

Excerpt:

How can we get smarter about machine learning?
As I said earlier, we’ve reached an important crossroads. Will we use new technologies to improve life for everyone, or to fuel the agendas of powerful people and organizations?

I certainly hope it’s the former. Few of us will run for president or lead a social media empire, but we can all help to move the needle.

Consume information with a critical eye.
Most people won’t stop using Facebook, Google, or social media platforms, so proceed with a healthy dose of skepticism. Remember that the internet can never be objective. Ask questions and come to your own conclusions.

Get your headlines from professional journalists.
Seek credible outlets for news about local, national and world events. I rely on the New York Times and the Wall Street Journal. You can pick your own sources, but don’t trust that the “article” your Aunt Marge just posted on Facebook is legit.

 

 

 

 

From MIT Technology Review on 4-2-2018

*Only* 14 percent of the world has to worry about robots taking their jobs. Yay?
The Organization for Economic Cooperation and Development (OECD) has released a major report analyzing the impact of automation on jobs in 32 countries.

Clashing views: In 2016, the OECD said only 9 percent of US and worldwide jobs face a “high degree of automobility.” That was a contradiction of one of the most widely cited reports on jobs and automation, by Oxford researchers Carl Frey and Michael Osborne, who in 2013 said that 47 percent of US jobs were at high risk of being consumed by automation.

What’s new: The OECD’s latest report says that across the countries analyzed, 14 percent of jobs are highly automatable, meaning they have over a 70 percent likelihood of automation. In the US, the study concludes that 10 percent of jobs will likely be lost to automation. An additional 32 percent of global jobs will be transformed and require significant worker retraining.

The big “but”: As the gap between the OECD report and Frey and Osborne’s estimates illustrate, predictions like these aren’t known for their accuracy. In fact, when we compiled all of the studies we could on the subject, we found there are about as many predictions as there are experts.

 


Also see:



Automation, skills use and training
— from oecd-ilibrary.org by Ljubica Nedelkoska and Glenda Quintini

Excerpts:

Here are the study’s key findings.
Across the 32 countries, close to one in two jobs are likely to be significantly affected by automation, based on the tasks they involve. But the degree of risk varies.

The variance in automatability across countries is large: 33% of all jobs in Slovakia are highly automatable, while this is only the case with 6% of the jobs in Norway.

The cross-country variation in automatability, contrary to expectations, is better explained by the differences in the organisation of job tasks within economic sectors, than by the differences in the sectoral structure of economies.

There are upside and downside risks to the figures obtained in this paper. On the upside, it is important to keep in mind that these estimates refer to technological possibilities, abstracting from the speed of diffusion and likelihood of adoption of such technologies….But there are risks on the downside too. First, the estimates are based on the fact that, given the current state of knowledge, tasks related to social intelligence, cognitive intelligence and perception and manipulation cannot be automated. However, progress is being made very rapidly, particularly in the latter two categories.

Most importantly, the risk of automation is not distributed equally among workers. Automation is found to mainly affect jobs in the manufacturing industry and agriculture, although a number of service sectors, such as postal and courier services, land transport and food services are also found to be highly automatable.

Overall, despite recurrent arguments that automation may start to adversely affect selected highly skilled occupations, this prediction is not supported by the Frey and Osborne (2013) framework of engineering bottlenecks used in this study. If anything, Artificial Intelligence puts more low-skilled jobs at risk than previous waves of technological progress…

A striking novel finding is that the risk of automation is the highest among teenage jobs. The relationship between automation and age is U-shaped, but the peak in automatability among youth jobs is far more pronounced than the peak among senior workers.


This unequal distribution of the risk of automation raises the stakes involved in policies to prepare workers for the new job requirements. In this context, adult learning is a crucial policy instrument for the re-training and up-skilling of workers whose jobs are being affected by technology. Unfortunately, evidence from this study suggests that a lot needs to be done to facilitate participation by the groups most affected by automation.

An analysis of German data suggests that training is used to move to jobs at lower risk of automation.

 

 
 

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