FTI 2020 Trend Report for Entertainment, Media, & Technology [FTI]

 

FTI 2020 Trend Report for Entertainment, Media, & Technology — from futuretodayinstitute.com

Our 3rd annual industry report on emerging entertainment, media and technology trends is now available.

  • 157 trends
  • 28 optimistic, pragmatic and catastrophic scenarios
  • 10 non-technical primers and glossaries
  • Overview of what events to anticipate in 2020
  • Actionable insights to use within your organization

KEY TAKEAWAYS

  • Synthetic media offers new opportunities and challenges.
  • Authenticating content is becoming more difficult.
  • Regulation is coming.
  • We’ve entered the post-fixed screen era.
  • Voice Search Optimization (VSO) is the new Search Engine Optimization (SEO).
  • Digital subscription models aren’t working.
  • Advancements in AI will mean greater efficiencies.

 

 

Emerging Tech Trend: Patient-Generated Health Data — from futuretodayinstitute.com — Newsletter Issue 124

Excerpt:

Near-Futures Scenarios (2023 – 2028):

Pragmatic: Big tech continues to develop apps that are either indispensably convenient, irresistibly addictive, or both, and we pay for them, not with cash, but with the data we (sometimes unwittingly) let the apps capture. But for the apps for health care and medical insurance, the stakes could literally be life-and-death. Consumers receive discounted premiums, co-pays, diagnostics and prescription fulfillment, but the data we give up in exchange leaves them more vulnerable to manipulation and invasion of privacy.

Catastrophic: Profit-driven drug makers exploit private health profiles and begin working with the Big Nine. They use data-based targeting to over prescribe patients, netting themselves billions of dollars. Big Pharma target and prey on people’s addictions, mental health predispositions and more, which, while undetectable on an individual level, take a widespread societal toll.

Optimistic: Health data enables prescient preventative care. A.I. discerns patterns within gargantuan data sets that are otherwise virtually undetectable to humans. Accurate predictive algorithms identifies complex combinations of risk factors for cancer or Parkinson’s, offers early screening and testing to high-risk patients and encourages lifestyle shifts or treatments to eliminate or delay the onset of serious diseases. A.I. and health data creates a utopia of public health. We happily relinquish our privacy for a greater societal good.

Watchlist: Amazon; Manulife Financial; GE Healthcare; Meditech; Allscripts; eClinicalWorks; Cerner; Validic; HumanAPI; Vivify; Apple; IBM; Microsoft; Qualcomm; Google; Medicare; Medicaid; national health systems; insurance companies.

 

Someone is always listening — from Future Today Institute

Excerpt:

Very Near-Futures Scenarios (2020 – 2022):

  • OptimisticBig tech and consumer device industries agree to a single set of standards to inform people when they are being listened to. Devices now emit an audible ping and/ or a visible light anytime they are actively recording sound. While they need to store data in order to improve natural language understanding and other important AI systems, consumers now have access to a portal and can see, listen to, and erase their data at any time. In addition, consumers can choose to opt-out of storing their data to help improve AI systems.
  • Pragmatic: Big tech and consumer device industries preserve the status quo, which leads to more cases of machine eavesdropping and erodes public trust. Federal agencies open investigations into eavesdropping practices, which leads to a drop in share prices and a concern that more advanced biometric technologies could face debilitating regulation.
  • CatastrophicBig tech and consumer device industries collect and store our conversations surreptitiously while developing new ways to monetize that data. They anonymize and sell it to developers wanting to create their own voice apps or to research institutions wanting to do studies using real-world conversation. Some platforms develop lucrative fee structures allowing others access to our voice data: business intelligence firms, market research agencies, polling agencies, political parties and individual law enforcement organizations. Consumers have little to no ability to see and understand how their voice data are being used and by whom. Opting out of collection systems is intentionally opaque. Trust erodes. Civil unrest grows.

Action Meter:

 

Watchlist:

  • Google; Apple; Amazon; Microsoft; Salesforce; BioCatch; CrossMatch; ThreatMetrix; Electronic Frontier Foundation; World Privacy Forum; American Civil Liberties Union; IBM; Baidu; Tencent; Alibaba; Facebook; Electronic Frontier Foundation; European Union; government agencies worldwide.

 

 

AI is in danger of becoming too male — new research — from singularityhub.com by Juan Mateos-Garcia and Joysy John

Excerpts (emphasis DSC):

But current AI systems are far from perfect. They tend to reflect the biases of the data used to train them and to break down when they face unexpected situations.

So do we really want to turn these bias-prone, brittle technologies into the foundation stones of tomorrow’s economy?

One way to minimize AI risks is to increase the diversity of the teams involved in their development. As research on collective decision-making and creativity suggests, groups that are more cognitively diverse tend to make better decisions. Unfortunately, this is a far cry from the situation in the community currently developing AI systems. And a lack of gender diversity is one important (although not the only) dimension of this.

A review published by the AI Now Institute earlier this year showed that less than 20 percent of the researchers applying to prestigious AI conferences are women, and that only a quarter of undergraduates studying AI at Stanford and the University of California at Berkeley are female.

 


From DSC:
My niece just left a very lucrative programming job and managerial role at Microsoft after working there for several years. As a single woman, she got tired of fighting the culture there. 

It was again a reminder to me that there are significant ramifications to the cultures of the big tech companies…especially given the power of these emerging technologies and the growing influence they are having on our culture.


Addendum on 8/20/19:

  • Google’s Hate Speech Detection A.I. Has a Racial Bias Problem — from fortunes.com by Jonathan Vanian
    Excerpt:
    A Google-created tool that uses artificial intelligence to police hate speech in online comments on sites like the New York Times has become racially biased, according to a new study. The tool, developed by Google and a subsidiary of its parent company, often classified comments written in the African-American vernacular as toxic, researchers from the University of Washington, Carnegie Mellon, and the Allen Institute for Artificial Intelligence said in a paper presented in early August at the Association for Computational Linguistics conference in Florence, Italy.
    .
  • On the positive side of things:
    Number of Female Students, Students of Color Tackling Computer Science AP on the Rise — from thejournal.com
 

A new immersive classroom uses AI and VR to teach Mandarin Chinese — from technologyreview.com by Karen Hao
Students will learn the language by ordering food or haggling with street vendors on a virtual Beijing street.

Excerpt:

Often the best way to learn a language is to immerse yourself in an environment where people speak it. The constant exposure, along with the pressure to communicate, helps you swiftly pick up and practice new vocabulary. But not everyone gets the opportunity to live or study abroad.

In a new collaboration with IBM Research, Rensselaer Polytechnic Institute (RPI), a university based in Troy, New York, now offers its students studying Chinese another option: a 360-degree virtual environment that teleports them to the busy streets of Beijing or a crowded Chinese restaurant. Students get to haggle with street vendors or order food, and the environment is equipped with different AI capabilities to respond to them in real time.

 

 

We Built an ‘Unbelievable’ (but Legal) Facial Recognition Machine — from nytimes.com by Sahil Chinoy

“The future of human flourishing depends upon facial recognition technology being banned,” wrote Woodrow Hartzog, a professor of law and computer science at Northeastern, and Evan Selinger, a professor of philosophy at the Rochester Institute of Technology, last year. ‘Otherwise, people won’t know what it’s like to be in public without being automatically identified, profiled, and potentially exploited.’ Facial recognition is categorically different from other forms of surveillance, Mr. Hartzog said, and uniquely dangerous. Faces are hard to hide and can be observed from far away, unlike a fingerprint. Name and face databases of law-abiding citizens, like driver’s license records, already exist. And for the most part, facial recognition surveillance can be set up using cameras already on the streets.” — Sahil Chinoy; per a weekly e-newsletter from Sam DeBrule at Machine Learnings in Berkeley, CA

Excerpt:

Most people pass through some type of public space in their daily routine — sidewalks, roads, train stations. Thousands walk through Bryant Park every day. But we generally think that a detailed log of our location, and a list of the people we’re with, is private. Facial recognition, applied to the web of cameras that already exists in most cities, is a threat to that privacy.

To demonstrate how easy it is to track people without their knowledge, we collected public images of people who worked near Bryant Park (available on their employers’ websites, for the most part) and ran one day of footage through Amazon’s commercial facial recognition service. Our system detected 2,750 faces from a nine-hour period (not necessarily unique people, since a person could be captured in multiple frames). It returned several possible identifications, including one frame matched to a head shot of Richard Madonna, a professor at the SUNY College of Optometry, with an 89 percent similarity score. The total cost: about $60.

 

 

 

 

From DSC:
What do you think about this emerging technology and its potential impact on our society — and on other societies like China? Again I ask…what kind of future do we want?

As for me, my face is against the use of facial recognition technology in the United States — as I don’t trust where this could lead.

This wild, wild, west situation continues to develop. For example, note how AI and facial recognition get their foot in the door via techs installed years ago:

The cameras in Bryant Park were installed more than a decade ago so that people could see whether the lawn was open for sunbathing, for example, or check how busy the ice skating rink was in the winter. They are not intended to be a security device, according to the corporation that runs the park.

So Amazon’s use of facial recognition is but another foot in the door. 

This needs to be stopped. Now.

 

Facial recognition technology is a menace disguised as a gift. It’s an irresistible tool for oppression that’s perfectly suited for governments to display unprecedented authoritarian control and an all-out privacy-eviscerating machine.

We should keep this Trojan horse outside of the city. (source)

 

Six global banks sign up to issue stablecoins on IBM’s now-live Blockchain Network — from cointelegraph.com by Marie Huillet

 

 

From DSC:
For the law schools, relevant lawyers, legislators, and judges out there…how soon before you are addressing blockchain-related issues, questions, and topics? My guess…? Sooner than you think.

 

 

Amazon is pushing facial technology that a study says could be biased — from nytimes.com by Natasha Singer
In new tests, Amazon’s system had more difficulty identifying the gender of female and darker-skinned faces than similar services from IBM and Microsoft.

Excerpt:

Over the last two years, Amazon has aggressively marketed its facial recognition technology to police departments and federal agencies as a service to help law enforcement identify suspects more quickly. It has done so as another tech giant, Microsoft, has called on Congress to regulate the technology, arguing that it is too risky for companies to oversee on their own.

Now a new study from researchers at the M.I.T. Media Lab has found that Amazon’s system, Rekognition, had much more difficulty in telling the gender of female faces and of darker-skinned faces in photos than similar services from IBM and Microsoft. The results raise questions about potential bias that could hamper Amazon’s drive to popularize the technology.

 

 

From DSC:
In this posting, I discussed an idea for a new TV show — a program that would be both entertaining and educational. So I suppose that this posting is a Part II along those same lines. 

The program that came to my mind at that time was a program that would focus on significant topics and issues within American society — offered up in a debate/presentation style format.

I had envisioned that you could have different individuals, groups, or organizations discuss the pros and cons of an issue or topic. The show would provide contact information for helpful resources, groups, organizations, legislators, etc. These contacts would be for learning more about a subject or getting involved with finding a solution for that problem.

OR

…as I revist that idea today…perhaps the show could feature humans versus an artificial intelligence such as IBM’s Project Debater:

 

 

Project Debater is the first AI system that can debate humans on complex topics. Project Debater digests massive texts, constructs a well-structured speech on a given topic, delivers it with clarity and purpose, and rebuts its opponent. Eventually, Project Debater will help people reason by providing compelling, evidence-based arguments and limiting the influence of emotion, bias, or ambiguity.

 

 

 

Big tech may look troubled, but it’s just getting started — from nytimes.com by David Streitfeld

Excerpt:

SAN JOSE, Calif. — Silicon Valley ended 2018 somewhere it had never been: embattled.

Lawmakers across the political spectrum say Big Tech, for so long the exalted embodiment of American genius, has too much power. Once seen as a force for making our lives better and our brains smarter, tech is now accused of inflaming, radicalizing, dumbing down and squeezing the masses. Tech company stocks have been pummeled from their highs. Regulation looms. Even tech executives are calling for it.

The expansion underlines the dizzying truth of Big Tech: It is barely getting started.

 

“For all intents and purposes, we’re only 35 years into a 75- or 80-year process of moving from analog to digital,” said Tim Bajarin, a longtime tech consultant to companies including Apple, IBM and Microsoft. “The image of Silicon Valley as Nirvana has certainly taken a hit, but the reality is that we the consumers are constantly voting for them.”

 

Big Tech needs to be regulated, many are beginning to argue, and yet there are worries about giving that power to the government.

Which leaves regulation up to the companies themselves, always a dubious proposition.

 

 

 

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.

 

 

 

Google Glass wasn’t a failure. It raised crucial concerns. — from wired.com by Rose Eveleth

Excerpts:

So when Google ultimately retired Glass, it was in reaction to an important act of line drawing. It was an admission of defeat not by design, but by culture.

These kinds of skirmishes on the front lines of surveillance might seem inconsequential — but they can not only change the behavior of tech giants like Google, they can also change how we’re protected under the law. Each time we invite another device into our lives, we open up a legal conversation over how that device’s capabilities change our right to privacy. To understand why, we have to get wonky for a bit, but it’s worth it, I promise.

 

But where many people see Google Glass as a cautionary tale about tech adoption failure, I see a wild success. Not for Google of course, but for the rest of us. Google Glass is a story about human beings setting boundaries and pushing back against surveillance…

 

IN THE UNITED States, the laws that dictate when you can and cannot record someone have a several layers. But most of these laws were written when smartphones and digital home assistants weren’t even a glimmer in Google’s eye. As a result, they are mostly concerned with issues of government surveillance, not individuals surveilling each other or companies surveilling their customers. Which means that as cameras and microphones creep further into our everyday lives, there are more and more legal gray zones.

 

From DSC:
We need to be aware of the emerging technologies around us. Just because we can, doesn’t mean we should. People need to be aware of — and involved with — which emerging technologies get rolled out (or not) and/or which features are beneficial to roll out (or not).

One of the things that’s beginning to alarm me these days is how the United States has turned over the keys to the Maserati — i.e., think an expensive, powerful thing — to youth who lack the life experiences to know how to handle such power and, often, the proper respect for such power. Many of these youthful members of our society don’t own the responsibility for the positive and negative influences and impacts that such powerful technologies can have.

If you owned the car below, would you turn the keys of this ~$137,000+ car over to your 16-25 year old? Yet that’s what America has been doing for years. And, in some areas, we’re now paying the price.

 

If you owned this $137,000+ car, would you turn the keys of it over to your 16-25 year old?!

 

The corporate world continues to discard the hard-earned experience that age brings…as they shove older people out of the workforce. (I hesitate to use the word wisdom…but in some cases, that’s also relevant/involved here.) Then we, as a society, sit back and wonder how did we get to this place?

Even technologists and programmers in their 20’s and 30’s are beginning to step back and ask…WHY did we develop this application or that feature? Was it — is it — good for society? Is it beneficial? Or should it be tabled or revised into something else?

Below is but one example — though I don’t mean to pick on Microsoft, as they likely have more older workers than the Facebooks, Googles, or Amazons of the world. I fully realize that all of these companies have some older employees. But the youth-oriented culture in American today has almost become an obsession — and not just in the tech world. Turn on the TV, check out the new releases on Netflix, go see a movie in a theater, listen to the radio, cast but a glance at the magazines in the check out lines, etc. and you’ll instantly know what I mean.

In the workplace, there appears to be a bias against older employees as being less innovative or tech-savvy — such a perspective is often completely incorrect. Go check out LinkedIn for items re: age discrimination…it’s a very real thing. But many of us over the age of 30 know this to be true if we’ve lost a job in the last decade or two and have tried to get a job that involves technology.

Microsoft argues facial-recognition tech could violate your rights — from finance.yahoo.com by Rob Pegoraro

Excerpt (emphasis DSC):

On Thursday, the American Civil Liberties Union provided a good reason for us to think carefully about the evolution of facial-recognition technology. In a study, the group used Amazon’s (AMZN) Rekognition service to compare portraits of members of Congress to 25,000 arrest mugshots. The result: 28 members were mistakenly matched with 28 suspects.

The ACLU isn’t the only group raising the alarm about the technology. Earlier this month, Microsoft (MSFT) president Brad Smith posted an unusual plea on the company’s blog asking that the development of facial-recognition systems not be left up to tech companies.

Saying that the tech “raises issues that go to the heart of fundamental human rights protections like privacy and freedom of expression,” Smith called for “a government initiative to regulate the proper use of facial recognition technology, informed first by a bipartisan and expert commission.”

But we may not get new laws anytime soon.

 

just because we can does not mean we should

 

Just because we can…

 

just because we can does not mean we should

 

Addendum on 12/27/18: — also related/see:

‘We’ve hit an inflection point’: Big Tech failed big-time in 2018 — from finance.yahoo.com by JP Mangalindan

Excerpt (emphasis DSC):

2018 will be remembered as the year the public’s big soft-hearted love affair with Big Tech came to a screeching halt.

For years, lawmakers and the public let massive companies like Facebook, Google, and Amazon run largely unchecked. Billions of people handed them their data — photos, locations, and other status-rich updates — with little scrutiny or question. Then came revelations around several high-profile data breaches from Facebook: a back-to-back series of rude awakenings that taught casual web-surfing, smartphone-toting citizens that uploading their data into the digital ether could have consequences. Google reignited the conversation around sexual harassment, spurring thousands of employees to walk out, while Facebook reminded some corners of the U.S. that racial bias, even in supposedly egalitarian Silicon Valley, remained alive and well. And Amazon courted well over 200 U.S. cities in its gaudy and protracted search for a second headquarters.

“I think 2018 was the year that people really called tech companies on the carpet about the way that they’ve been behaving conducting their business,” explained Susan Etlinger, an analyst at the San Francisco-based Altimeter Group. “We’ve hit an inflection point where people no longer feel comfortable with the ways businesses are conducting themselves. At the same time, we’re also at a point, historically, where there’s just so much more willingness to call out businesses and institutions on bigotry, racism, sexism and other kinds of bias.”

 

The public’s love affair with Facebook hit its first major rough patch in 2016 when Russian trolls attempted to meddle with the 2016 U.S. presidential election using the social media platform. But it was the Cambridge Analytica controversy that may go down in internet history as the start of a series of back-to-back, bruising controversies for the social network, which for years, served as the Silicon Valley poster child of the nouveau American Dream. 

 

 

AI Now Report 2018 | December 2018  — from ainowinstitute.org

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendations that can help create accountability frameworks capable of governing these powerful technologies.

  1. Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.
  2. Facial recognition and affect recognition need stringent regulation to protect the public interest.
  3. The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.
  4. AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.
  5. Technology companies should provide protections for conscientious objectors, employee organizing, and ethical whistleblowers.
  6.  Consumer protection agencies should apply “truth-in-advertising” laws to AI products and services.
  7. Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.
  8. Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”
  9. More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.
  10. University AI programs should expand beyond computer science and engineering disciplines. AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

 

Also see:

After a Year of Tech Scandals, Our 10 Recommendations for AI — from medium.com by the AI Now Institute
Let’s begin with better regulation, protecting workers, and applying “truth in advertising” rules to AI

 

Also see:

Excerpt:

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

 

From DSC:
This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them! 

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

 

 

 

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.

 


 

 

Incumbents Strike Back: Insights from the Global C-suite Study — by the IBM Institute for Business Value

Excerpts:

Dancing with disruption
Incumbents hit their stride
We explore the forces at play in shaping the current competitive environment, the opportunities emerging, and how a balance between stability and dynamism favors the Reinventors.

Trust in the journey
The path to personalization
Here we show how the Reinventors as design thinkers are testing their assumptions and re-orienting their organizations to engage their customers and create bonds based on trust.

Orchestrating the future
The pull of platform business models
This section reveals the step change in capability that occurs as organizations scale their partner networks in new ways. We chart how organizations will need to reconsider their value propositions and allocation of resources to own or participate in platforms.

Innovation in motion
Agility for the enterprise
We delineate how leaders are liberating their employees to experiment and innovate, get up close to customers and thrive in an ever-evolving ecosystem of dynamic teams and partnerships.

 

 

 

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