Microsoft rolls out healthcare bot: How it will change healthcare industry — from yourtechdiet.com by Brian Curtis

Excerpt:

AI and the Healthcare Industry
This technology is evidently the game changer in the healthcare industry. According to the reports by Frost & Sullivan, the AI market for healthcare is likely to experience a CAGR of 40% by 2021, and has the potential to change industry outcomes by 30-40%, while cutting treatment costs in half.

In the words of Satya Nadella, “AI is the runtime that is going to shape all of what we do going forward in terms of the applications as well as the platform advances”.

Here are a few ways Microsoft’s Healthcare Bot will shape the Healthcare Industry…

 

Also see:

  • Why AI will make healthcare personal — from weforum.org by Peter Schwartz
    Excerpt:
    Digital assistants to provide a 24/7 helping hand
    The digital assistants of the future will be full-time healthcare companions, able to monitor a patient’s condition, transmit results to healthcare providers, and arrange virtual and face-to-face appointments. They will help manage the frequency and dosage of medication, and provide reliable medical advice around the clock. They will remind doctors of patients’ details, ranging from previous illnesses to past drug reactions. And they will assist older people to access the care they need as they age, including hospice care, and help to mitigate the fear and loneliness many elderly people feel.

 

  • Introducing New Alexa Healthcare Skills — from developer.amazon.com by Rachel Jiang
    Excerpts:
    The new healthcare skills that launched today are:Express Scripts (a leading Pharmacy Services Organization)
    Cigna Health Today (by Cigna, the global health service company)
    My Children’s Enhanced Recovery After Surgery (ERAS) (by Boston Children’s Hospital, a leading children’s hospital)
    Swedish Health Connect (by Providence St. Joseph Health, a healthcare system with 51 hospitals across 7 states and 829 clinics)
    Atrium Health (a healthcare system with more than 40 hospitals and 900 care locations throughout North and South Carolina and Georgia)
    Livongo (a leading consumer digital health company that creates new and different experiences for people with chronic conditions)

Voice as the Next Frontier for Conveniently Accessing Healthcare Services

 

  • Got health care skills? Big Tech wants to hire you — from linkedin.com Jaimy Lee
    Excerpt:
    As tech giants like Amazon, Apple and Google place bigger and bigger bets on the U.S. health care system, it should come as no surprise that the rate at which they are hiring workers with health care skills is booming.We took a deep dive into the big tech companies on this year’s LinkedIn Top Companies list in the U.S., uncovering the most popular health care skills among their workers — and what that says about the future of health care in America.
 

The growing marketplace for AI ethics — from forbes.com by Forbes Insights with Intel AI

Excerpt:

As companies have raced to adopt artificial intelligence (AI) systems at scale, they have also sped through, and sometimes spun out, in the ethical obstacle course AI often presents.

AI-powered loan and credit approval processes have been marred by unforeseen bias. Same with recruiting tools. Smart speakers have secretly turned on and recorded thousands of minutes of audio of their owners.

Unfortunately, there’s no industry-standard, best-practices handbook on AI ethics for companies to follow*—at least not yet. Some large companies, including Microsoft and Google, are developing their own internal ethical frameworks.

A number of think tanks, research organizations, and advocacy groups, meanwhile, have been developing a wide variety of ethical frameworks and guidelines for AI.

 

*Insert DSC:
Read this as a very powerful, chaotic, massive WILD, WILD, WEST.  Can law schools, legislatures, governments, businesses, and more keep up with this new pace of technological change?

 

Also see:

 

Artificial intelligence seeing massive surge in education — from campustechnology.com by David Nagel

Excerpt:

Education will experience the third-largest growth of any sector, coming in slightly behind government (44.3 percent) and “personal and consumer services” (43.3 percent).

The top use cases for AI at present, based on current market share, are:

  • Automated customer service agents (12.5 percent);
  • Sales process recommendation and automation (7.6 percent);
  • Automated threat intelligence and prevention systems (7.5 percent);
  • Program advisors and recommendation systems (6.4 percent); and
  • Automated preventative maintenance, diagnosis and treatment systems (6.2 percent).

 

 

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Is Thomas Frey right? “…by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet.”

From a fairly recent e-newsletter from edsurge.com — though I don’t recall the exact date (emphasis DSC):

New England is home to some of the most famous universities in the world. But the region has also become ground zero for the demographic shifts that promise to disrupt higher education.

This week saw two developments that fit the narrative. On Monday, Southern Vermont College announced that it would shut its doors, becoming the latest small rural private college to do so. Later that same day, the University of Massachusetts said it would start a new online college aimed at a national audience, noting that it expects campus enrollments to erode as the number of traditional college-age students declines in the coming years.

“Make no mistake—this is an existential threat to entire sectors of higher education,” said UMass president Marty Meehan in announcing the online effort.

The approach seems to parallel the U.S. retail sector, where, as a New York Times piece outlines this week, stores like Target and WalMart have thrived by building online strategies aimed at competing with Amazon, while stores like Gap and Payless, which did little to move online, are closing stores. Of course, college is not like any other product or service, and plenty of campuses are touting the richness of the experience that students get by actually coming to a campus. And it’s not clear how many colleges can grow online to a scale that makes their investments pay off.

 

“It’s predicted that over the next several years, four to five major national players with strong regional footholds will be established. We intend to be one of them.”

University of Massachusetts President Marty Meehan

 

 

From DSC:
That last quote from UMass President Marty Meehan made me reflect upon the idea of having one or more enormous entities that will provide “higher education” in the future. I wonder if things will turn out to be that we’ll have more lifelong learning providers and platforms in the future — with the idea of a 60-year curriculum being an interesting idea that may come into fruition.

Long have I predicted that such an enormous entity would come to pass. Back in 2008, I named it the Forthcoming Walmart of Education. But then as the years went by, I got bumbed out on some things that Walmart was doing, and re-branded it the Forthcoming Amazon.com of Higher Education. We’ll see how long that updated title lasts — but you get the point. In fact, the point aligns very nicely with what futurist Thomas Frey has been predicting for years as well:

“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider. (source)

I realize that education doesn’t always scale well…but I’m thinking that how people learn in the future may be different than how we did things in the past…communities of practice comes to mind…as does new forms of credentialing…as does cloud-based learner profiles…as does the need for highly efficient, cost-effective, and constant opportunities/means to reinvent oneself.

Also see:

 

 

Addendum:

74% of consumers go to Amazon when they’re ready to buy something. That should be keeping retailers up at night. — from cnbc.com

Key points (emphasis DSC)

  • Amazon remains a looming threat for some of the biggest retailers in the country — like Walmart, Target and Macy’s.
  • When consumers are ready to buy a specific product, nearly three-quarters of them, or 74 percent, are going straight to Amazon to do it, according to a new study by Feedvisor.
  • By the end of this year, Amazon is expected to account for 52.4 percent of the e-commerce market in the U.S., up from 48 percent in 2018.

 

“In New England, there will be between 32,000 and 54,000 fewer college-aged students just seven years from now,” Meehan said. “That means colleges and universities will have too much capacity and not enough demand at a time when the economic model in higher education is already straining under its own weight.” (Marty Meehan at WBUR)

 

 

A Chinese subway is experimenting with facial recognition to pay for fares — from theverge.com by Shannon Liao

Excerpt:

Scanning your face on a screen to get into the subway might not be that far off in the future. In China’s tech capital, Shenzhen, a local subway operator is testing facial recognition subway access, powered by a 5G network, as spotted by the South China Morning Post.

The trial is limited to a single station thus far, and it’s not immediately clear how this will work for twins or lookalikes. People entering the station can scan their faces on the screen where they would normally have tapped their phones or subway cards. Their fare then gets automatically deducted from their linked accounts. They will need to have registered their facial data beforehand and linked a payment method to their subway account.

 

 

From DSC:
I don’t want this type of thing here in the United States. But…now what do I do? What about you? What can we do? What paths are open to us to stop this?

I would argue that the new, developing, technological “Wild Wests” in many societies throughout the globe could be dangerous to our futures. Why? Because the pace of change has changed. And these new Wild Wests now have emerging, powerful, ever-more invasive (i.e., privacy-stealing) technologies to deal with — the likes of which the world has never seen or encountered before. With this new, rapid pace of change, societies aren’t able to keep up.

And who is going to use the data? Governments? Large tech companies? Other?

Don’t get me wrong, I’m generally pro-technology. But this new pace of change could wreak havoc on us. We need time to weigh in on these emerging techs.

 

Addendum on 3/20/19:

  • Chinese Facial Recognition Database Exposes 2.5 Million People — from futurumresearch.com by Shelly Kramer
    Excerpt:
    An artificial intelligence company operating a facial recognition system in China recently left its database exposed online, leaving the personal information of some 2.5 million Chinese citizens vulnerable. Considering how much the Chinese government relies on facial recognition technology, this is a big deal—for both the Chinese government and Chinese citizens.

 

 

How MIT’s Mini Cheetah Can Help Accelerate Robotics Research — from spectrum.ieee.org by Evan Ackerman
Sangbae Kim talks to us about the new Mini Cheetah quadruped and his future plans for the robot

 

 

From DSC:
Sorry, but while the video/robot is incredible, a feeling in the pit of my stomach makes me reflect upon what’s likely happening along these lines in the militaries throughout the globe…I don’t mean to be a fear monger, but rather a realist.

 

 

Instructure: Plans to expand beyond Canvas LMS into machine learning and AI — from mfeldstein.com by Phill Hill

Excerpts:

On the same day as Instructure’s earnings call and release of FY2018 financial results, the company announced the acquisition of Portfolium for $43 million, a small startup focusing on “ePortfolio network, student-centered assessment, job matching capabilities, and academic and co-curricular pathways”.

Instructure now views itself as a company with a suite of products, and they are much more open to using corporate M&A to build this portfolio.

We already have analytical capabilities in our Canvas platform. I want to be really clear and delineate the difference between an analytics and reporting capability, and a machine learning and AI platform.

We have the most comprehensive database on the educational experience in the globe. So given that information that we have, no one else has those data assets at their fingertips to be able to develop those algorithms and predictive models.

What’s even more interesting and compelling is that we can take that information, correlate it across all sorts of universities, curricula, etc, and we can start making recommendations and suggestions to the student or instructor in how they can be more successful. Watch this video, read this passage, do problems 17-34 in this textbook, spend an extra two hours on this or that. When we drive student success, we impact things like retention, we impact the productivity of the teachers, and it’s a huge opportunity. That’s just one small example. Our DIG initiative, it is first and foremost a platform for ML and AI, and we will deliver and monetize it by offering different functional domains of predictive algorithms and insights. Maybe things like student success, retention, coaching and advising, career pathing, as well as a number of the other metrics that will help improve the value of an institution or connectivity across institutions.

 

 

 

 

Why AI is a threat to democracy — and what we can do to stop it — from technologyreview.com by Karen Hao and Amy Webb

Excerpt:

Universities must create space in their programs for hybrid degrees. They should incentivize CS students to study comparative literature, world religions, microeconomics, cultural anthropology and similar courses in other departments. They should champion dual degree programs in computer science and international relations, theology, political science, philosophy, public health, education and the like. Ethics should not be taught as a stand-alone class, something to simply check off a list. Schools must incentivize even tenured professors to weave complicated discussions of bias, risk, philosophy, religion, gender, and ethics in their courses.

One of my biggest recommendations is the formation of GAIA, what I call the Global Alliance on Intelligence Augmentation. At the moment people around the world have very different attitudes and approaches when it comes to data collection and sharing, what can and should be automated, and what a future with more generally intelligent systems might look like. So I think we should create some kind of central organization that can develop global norms and standards, some kind of guardrails to imbue not just American or Chinese ideals inside AI systems, but worldviews that are much more representative of everybody.

Most of all, we have to be willing to think about this much longer-term, not just five years from now. We need to stop saying, “Well, we can’t predict the future, so let’s not worry about it right now.” It’s true, we can’t predict the future. But we can certainly do a better job of planning for it.

 

 

 

Police across the US are training crime-predicting AIs on falsified data — from technologyreview.com by Karen Hao
A new report shows how supposedly objective systems can perpetuate corrupt policing practices.

Excerpts (emphasis DSC):

Despite the disturbing findings, the city entered a secret partnership only a year later with data-mining firm Palantir to deploy a predictive policing system. The system used historical data, including arrest records and electronic police reports, to forecast crime and help shape public safety strategies, according to company and city government materials. At no point did those materials suggest any effort to clean or amend the data to address the violations revealed by the DOJ. In all likelihood, the corrupted data was fed directly into the system, reinforcing the department’s discriminatory practices.


But new research suggests it’s not just New Orleans that has trained these systems with “dirty data.” In a paper released today, to be published in the NYU Law Review, researchers at the AI Now Institute, a research center that studies the social impact of artificial intelligence, found the problem to be pervasive among the jurisdictions it studied. This has significant implications for the efficacy of predictive policing and other algorithms used in the criminal justice system.

“Your system is only as good as the data that you use to train it on,” says Kate Crawford, cofounder and co-director of AI Now and an author on the study.

 

How AI is enhancing wearables — from techopedia.com by Claudio Butticev
Takeaway: Wearable devices have been helping people for years now, but the addition of AI to these wearables is giving them capabilities beyond anything seen before.

Excerpt:

Restoring Lost Sight and Hearing – Is That Really Possible?
People with sight or hearing loss must face a lot of challenges every day to perform many basic activities. From crossing the street to ordering food on the phone, even the simplest chore can quickly become a struggle. Things may change for these struggling with sight or hearing loss, however, as some companies have started developing machine learning-based systems to help the blind and visually impaired find their way across cities, and the deaf and hearing impaired enjoy some good music.

German AI company AiServe combined computer vision and wearable hardware (camera, microphone and earphones) with AI and location services to design a system that is able to acquire data over time to help people navigate through neighborhoods and city blocks. Sort of like a car navigation system, but in a much more adaptable form which can “learn how to walk like a human” by identifying all the visual cues needed to avoid common obstacles such as light posts, curbs, benches and parked cars.

 

From DSC:
So once again we see the pluses and minuses of a given emerging technology. In fact, most technologies can be used for good or for ill. But I’m left with asking the following questions:

  • As citizens, what do we do if we don’t like a direction that’s being taken on a given technology or on a given set of technologies? Or on a particular feature, use, process, or development involved with an emerging technology?

One other reflection here…it’s the combination of some of these emerging technologies that will be really interesting to see what happens in the future…again, for good or for ill. 

The question is:
How can we weigh in?

 

Also relevant/see:

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

Excerpt:

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.

 

Furthermore, it is long overdue for technology companies to directly address the cultures of exclusion and discrimination in the workplace. The lack of diversity and ongoing tactics of harassment, exclusion, and unequal pay are not only deeply harmful to employees in these companies but also impacts the AI products they release, producing tools that perpetuate bias and discrimination.

The current structure within which AI development and deployment occurs works against meaningfully addressing these pressing issues. Those in a position to profit are incentivized to accelerate the development and application of systems without taking the time to build diverse teams, create safety guardrails, or test for disparate impacts. Those most exposed to harm from 42 these systems commonly lack the financial means and access to accountability mechanisms that would allow for redress or legal appeals. 233 This is why we are arguing for greater funding for public litigation, labor organizing, and community participation as more AI and algorithmic systems shift the balance of power across many institutions and workplaces.

 

Also relevant/see:

 

 

Getting smart about the future of AI — from technologyreview.com by MIT Technology Review Insights
Artificial intelligence is a primary driver of possibilities and promise as the Fourth Industrial Revolution unfolds.

Excerpts:

The Industrial Revolution conjures up images of steam engines, textile mills, and iron workers. This was a defining period during the late 18th and early 19th centuries, as society shifted from primarily agrarian to factory-based work. A second phase of rapid industrialization occurred just before World War I, driven by growth in steel and oil production, and the emergence of electricity.

Fast-forward to the 1980s, when digital electronics started having a deep impact on society—the dawning Digital Revolution. Building on that era is what’s called the Fourth Industrial Revolution. Like its predecessors, it is centered on technological advancements—this time it’s artificial intelligence (AI), autonomous machines, and the internet of things—but now the focus is on how technology will affect society and humanity’s ability to communicate and remain connected.

 

That’s what AI technologies represent in the current period of technological change. It is now critical to carefully consider the future of AI, what it will look like, the effect it will have on human life, and what challenges and opportunities will arise as it evolves.

 

 

See the full report here >>

 

 

Also see:

  • Where Next for AI In Business? An overview for C-level executives — from techrevolution.asia by Bernard Marr
    Excerpt:
    The AI revolution is now well underway. In finance, marketing, medicine and manufacturing, machines are learning to monitor and adapt to real-world inputs in order to operate more efficiently, without human intervention. In our everyday lives, AI kicks in whenever we search the internet, shop online or settle down on the sofa to watch Netflix or listen to Spotify. At this point, it’s safe to say that AI is no longer the preserve of science fiction, but has already changed our world in a huge number of different ways.So: what next? Well, the revolution is showing no signs of slowing down. Research indicates that businesses, encouraged by the initial results they have seen, are now planning on stepping up investment and deployment of AI.One of the most noticeable advances will be the ongoing “democratization” of AI. What this means, put simply, is that AI-enabled business tools will increasingly become available to all of us, no matter what jobs we do.

 

You’ll no longer need to be an expert in computer science to use AI to do your job efficiently – this is the “democratization” of AI and it’s a trend which will impact more and more businesses going forward.

 

 

The real reason tech struggles with algorithmic bias — from wired.com by Yael Eisenstat

Excerpts:

ARE MACHINES RACIST? Are algorithms and artificial intelligence inherently prejudiced? Do Facebook, Google, and Twitter have political biases? Those answers are complicated.

But if the question is whether the tech industry doing enough to address these biases, the straightforward response is no.

Humans cannot wholly avoid bias, as countless studies and publications have shown. Insisting otherwise is an intellectually dishonest and lazy response to a very real problem.

In my six months at Facebook, where I was hired to be the head of global elections integrity ops in the company’s business integrity division, I participated in numerous discussions about the topic. I did not know anyone who intentionally wanted to incorporate bias into their work. But I also did not find anyone who actually knew what it meant to counter bias in any true and methodical way.

 

But the company has created its own sort of insular bubble in which its employees’ perception of the world is the product of a number of biases that are engrained within the Silicon Valley tech and innovation scene.

 

 

AI bias: 9 questions leaders should ask — from enterprisersproject.com by Kevin Casey
Artificial intelligence bias can create problems ranging from bad business decisions to injustice. Use these questions to fight off potential biases in your AI systems.

Excerpt:

People questions to ask about AI bias
1. Who is building the algorithms?
2. Do your AI & ML teams take responsibility for how their work will be used?
3. Who should lead an organization’s effort to identify bias in its AI systems?
4. How is my training data constructed?

Data questions to ask about AI bias
5. Is the data set comprehensive?
6. Do you have multiple sources of data?

Management questions to ask about AI bias
7. What proportion of resources is appropriate for an organization to devote to assessing potential bias?
8. Have you thought deeply about what metrics you use to evaluate your work?
9. How can we test for bias in training data?

 

 

13 industries soon to be revolutionized by artificial intelligence — from forbes.com by the Forbes Technology Council

Excerpt:

Artificial intelligence (AI) and machine learning (ML) have a rapidly growing presence in today’s world, with applications ranging from heavy industry to education. From streamlining operations to informing better decision making, it has become clear that this technology has the potential to truly revolutionize how the everyday world works.

While AI and ML can be applied to nearly every sector, once the technology advances enough, there are many fields that are either reaping the benefits of AI right now or that soon will be. According to a panel of Forbes Technology Council members, here are 13 industries that will soon be revolutionized by AI.

 

 

 

 

Emerging technology trends can seem both elusive and ephemeral, but some become integral to business and IT strategies—and form the backbone of tomorrow’s technology innovation. The eight chapters of Tech Trends 2019 look to guide CIOs through today’s most promising trends, with an eye toward innovation and growth and a spotlight on emerging trends that may well offer new avenues for pursuing strategic ambitions.

 

 

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