IT careers: 8 hot jobs in 2021 — from enterprisersproject.com by Stephanie Overby
Both IT job seekers and hiring managers need to understand what’s in high demand. Cloud, security, data, and AI skills star on the list of 2021’s hottest jobs, say IT recruiters and leaders

Excerpts:

  1. Artificial Intelligence (AI) specialists
  2. Strategy-minded software developers and managers
  3. Business-focused data scientists
  4. Data engineers
  5. AIOps analysts, engineers, and architects
  6. Cybersecurity architects and engineers
  7. Cloud architects
  8. IT directors who demonstrate soft skills
 

The AI Roundup – Top 15 Blogs of 2020 — from blog.re-work.co

Excerpt:

Below we have rounded up our 15 most-read blogs of the year, including must-read papers suggestions from AI experts, advice for those starting out in AI, Netflix predictive algorithms and more. See a summary of each blog and link below!

 

From DSC:
An interesting, more positive use of AI here:

Deepdub uses AI to dub movies in the voice of famous actors — from protocol.com by Janko Roettgers
Fresh out of stealth, the startup is using artificial intelligence to automate the localization process for global streaming.

Excerpt:

Tel Aviv-based startup Deepdub wants to help streaming services accelerate this kind of international rollout by using artificial intelligence for their localization needs. Deepdub, which came out of stealth on Wednesday, has built technology that can translate a voice track to a different language, all while staying true to the voice of the talent. This makes it possible to have someone like Morgan Freeman narrate a movie in French, Italian or Russian without losing what makes Freeman’s voice special and recognizable.

From DSC:
A much more negative use of AI here:

A much more negative use of AI here...

 

 

Can algorithms save college admissions?

Can Algorithms Save College Admissions? — from chronicle.com by Brian Rosenberg
We’ve tried a system based on competition long enough. It isn’t working.

Excerpt (emphasis DSC):

Here is an alternative and much more radical proposal: What if we replaced the current and longstanding admissions process among private colleges with a match process, similar to what has for years been used to match medical-school graduates with residency and fellowship positions? What if, in other words, we used data and algorithms instead of travel, merit aid, and free food to drive college admissions?

From DSC:
Love the “What if…” thinking here and the spirit of innovation behind it. I wonder if AI and cloud-based learner profiles might play into something like this in the future…?

Also see:

7 Ways To Make College Admissions More Equitable — from stradaeducation.org by Patty Reinert Mason and Jeff Selingo
Is it time to reconsider early-decision applications, legacy preferences, and reliance on feeder high schools?
Selingo offers these practical steps colleges and universities can take to make admissions more equitable:

  • Eliminate early-decision applications.
  • Be upfront about what you’re looking for in this year’s incoming class so students and parents have the information they need.
  • Be transparent about what it costs to study at your school.
  • Look beyond traditional “feeder high schools” for recruitment, creating opportunity for a more diverse group of students.
  • Reduce preferences given to athletes and legacies.
  • Rethink application requirements to put more emphasis on high school coursework and grades and less on extracurriculars, recommendations, and essays.
  • Expand the size of freshman classes.

Also see:

 

Report: There’s More to Come for AI in Ed — from thejournal.com by Dian Schaffhauser

Excerpts:

The group came up with dozens of “opportunities” for AI in education, from extending what teachers can do to better understanding human learning:

  • Using virtual instructors to free up “personalization time” for classroom teachers;
  • Offloading the “cognitive load” of teaching;
  • Providing “job aids” for teachers;
  • Identifying the links between courses, credentials, degrees and skills;
  • “Revolutionizing” testing and assessment;
  • Creating new kinds of “systems of support”;
  • Helping with development of “teaching expertise”; and
  • Better understanding human learning through “modeling and building interfaces” in AI.

But contributors also offered just as many barriers to success:

  • Differences in the way teachers teach would require “different job aids”;
  • Teachers would fear losing their jobs;
  • Data privacy concerns;
  • Bias worries;
  • Dealing with unrealistic expectations and fears about AI pushed in “popular culture”;
  • Lack of diversity in gender, ethnicity and culture in AI projects; and
  • Smart use of data would require more teacher training.
 

From DSC:
The good…

London A.I. lab claims breakthrough that could accelerate drug discovery — from nytimes.com by
Researchers at DeepMind say they have solved “the protein folding problem,” a task that has bedeviled scientists for more than 50 years

This long-sought breakthrough could accelerate the ability to understand diseases, develop new medicines and unlock mysteries of the human body.

…and the not so good…

 

The State of AI in 2020 -- from McKinsey and Company

Where AI is being used most in 2020

From DSC:
I saw this item out at:

  • AI is delivering a growing share of earnings, says McKinsey — from which-50.com by Andrew Birmingham
    Excerpt:
    Some companies are generating an increasing share of the profits in a way that is directly attributable to AI, and the best performers are likely to increase their investments setting up a world of algorithmic leaders and laggards, according to a new paper from McKinsey & Company. Called The State of AI in 2020, the report notes that we could start to see a widening divide between AI leaders and the majority of companies still struggling to capitalise on the technology.

Also see:

 

The Observatory is an interactive platform that allows you to do a preliminary analysis of 600+ legal technologies in the market today

The Observatory — from orrick.com with thanks to Gabe Teninbaum for mentioning this resource in his Lawtomatic Newsletter (Issue #112, 11/18/20)

The Observatory is an interactive platform that allows you to do a preliminary analysis of 600+ legal technologies in the market today (including some developed by Orrick):

  • Gain insight into features of legal tools
  • View leading categories of legal tech, from artificial intelligence to workflow automation
  • Understand tech use-cases for litigation, transactional and general solutions
  • Identify legal tech companies with diverse leadership

Excerpt from Gabe’s newsletter:

  • The Observatory: the tech-savvy biglaw firm, Orrick, has a new interactive platform offering data on 600+ legal technologies currently on the market.  A user can click on the type of tool they’d like to learn more about (e.g. document automation or contract management), click on various filters, then get a summary of what it does.  It also includes a narrative box for what makes the tool unique.  It’s easy to use, free, and also gives a nice preview for clients on the type of value the firm might offer them beyond run-of-the-mill representation.

Explore The Observatory from Orrick dot com to help you identify potential fits for your legaltech related needs

 

AI Conversations: Enabling Smarter, More Efficient Healthcare — from cio.com

Excerpt:

Healthcare providers face a wide range of critical challenges in delivering quality healthcare while containing rising costs. Many forward-looking providers are using artificial intelligence to streamline workflows, improve diagnostics, personalize medicine and reduce the length of hospital stays.

 

The Dice Q3 Tech Job Report | Tech Hiring and COVID-19: What You Need to Know

The Dice Q3 Tech Job Report Tech Hiring and COVID-19: What You Need to Know

The Dice Q3 Tech Job Report: Tech Hiring and COVID-19: What You Need to Know — from techhub.dice.com
The report, issued quarterly by Dice, provides exclusive statistics and analysis on the tech hiring landscape, including top cities and states, top employers and the most sought-after skills and occupations.

From DSC:
One can quickly see how valuable this information would be as a data feed into an AI-based, next-generation learning platform.

The platform would connect the marketable skills with the courses, websites, blogs, RSS feeds/streams of content, etc. that would help a learner quickly and affordably build such in-demand skills. Given the shortening half-lives of many kinds of information, such a service is needed desperately…especially now with the impact of the Coronavirus.

Also relevant: See how ISTE built its upcoming virtual event!

 

Temperament-Inclusive Pedagogy: Helping Introverted and Extraverted Students Thrive in a Changing Educational Landscape — from onlinelearningconsortium.org by Mary R. Fry

Excerpt (emphasis DSC):

So how do we take these different approaches to learning into account and foster a classroom environment that is more inclusive of the needs of both extraverts and introverts? Let’s first distinguish between how extraverts and introverts most prefer to learn, and then discuss ways to meet the needs of both. Extraverts tend to learn through active and social engagement with the material (group work, interactive learning experiences, performing and discussing). Verbalizing typically helps extraverts to think through their ideas and to foster new ones. They often think quickly on their feet and welcome working in large groups. It can be challenging for extraverts to generate ideas in isolation (talking through ideas is often needed) and thus working on solitary projects and writing can be challenging.

In contrast, introverts thrive with solitary/independent work and typically need this time to sort through what they are learning before they can formulate their thoughts and articulate their perspectives. Introverted learners often dislike group work (or at least the group sizes and structures that are often used in the classroom (more on this in a moment)) and find their voice drowned out in synchronous discussions as they don’t typically think as fast as their extroverted counterparts and don’t often speak until they feel they have something carefully thought out to share. Introverted learners are often quite content, and can remain attentive, through longer lectures and presentations and prefer engaging with the material in a more interactive way only after a pause or break.

From DSC:
Could/would a next-generation learning platform that has some Artificial Intelligence (AI) features baked into it — working in conjunction with a cloud-based learner profile — be of assistance here?

That is, maybe a learner could self-select the type of learning that they are: introverted or extroverted. Or perhaps they could use a sliding scaled to mix learning activities up to a certain degree. Or perhaps if one wasn’t sure of their preferences, they could ask the AI-backed system to scan for how much time they spent doing learning activities X, Y, and Z versus learning activities A, B, and C…then AI could offer up activities that meet a learner’s preferences.

(By the way, I love the idea of the “think-ink-pair-share” — to address both extroverted and introverted learners. This can be done digitally/virtually as well as in a face-to-face setting.)

All of this would further assist in helping build an enjoyment of learning. And wouldn’t that be nice? Now that we all need to learn for 40, 50, 60, 70, or even 80 years of our lives?

The 60-Year Curriculum: A Strategic Response to a Crisis

 

The State of AI in Higher Education — from campustechnology.com by Dian Schaffhauser
Both industry and higher ed experts see opportunities and risk, hype and reality with AI for teaching and learning.

Excerpts:

Kurt VanLehn, the chair for effective education in STEM in the School of Computing, Informatics and Decision Systems Engineering at Arizona State University, knows how challenging it can be people to come up with examples of effective AI in education. Why? “Because learning is complicated.”

Nuno Fernandes, president and CEO of Ilumno, an ed tech company in Latin America, isn’t ready to count adaptive learning out yet, if only because adaptivity has worked in other industries, such as social platforms like Netflix and Amazon, to identify what could work best for the user, based on previous activities and preferred formats of curriculum.

As Ilumno’s Fernandes asserted, AI won’t “substitute for faculty in any of our lifetimes. What it will do is give us tools to work better and to complement what is being done by humans.”

From DSC:
The article is a very balanced one. On one hand, it urges caution and points out that learning is messy and complex. On the other hand, it points out some beneficial applications of AI that already exist in language learning and in matching alumni with students for mentorship-related reasons.

From my perspective, I think AI-based systems will be used to help us scan job descriptions to see what the marketplace needs and is calling for. Such a system would be a major step forward in at least pointing out the existing hiring trends, needed skillsets, job openings, and more — and to do so in REAL-TIME!

Colleges, universities, and alternatives to traditional higher education could use this information to be far more responsive to the needs of the workplace. Then, such systems could match what the workplace needs with courses, microlearning-based feeds, apprenticeships, and other sources of learning that would help people learn those in-demand skills.

That in and of itself is HUGE. Again, HUGE. Given the need for people to reinvent themselves — and to do so quickly and affordably — that is incredibly beneficial.

Also, I do think there will be cloud-based learner profiles…data that each of us control and say who has access to it. Credentials will be stored there, for example. AI-based systems can scan such profiles and our desired career goals and suggest possible matches.

We can change our career goals. We don’t have to be locked into a particular track or tracks. We can reinvent ourselves. In fact, many of us will have to.

 

From DSC:
Who needs to be discussing/debating “The Social Dilemma” movie? Whether one agrees with the perspectives put forth therein or not, the discussion boards out there should be lighting up in the undergraduate areas of Computer Science (especially Programming), Engineering, Business, Economics, Mathematics, Statistics, Philosophy, Religion, Political Science, Sociology, and perhaps other disciplines as well. 

To those starting out the relevant careers here…just because we can, doesn’t mean we should. Ask yourself not whether something CAN be developed, but *whether it SHOULD be developed* and what the potential implications of a technology/invention/etc. might be. I’m not aiming to take a position here. Rather, I’m trying to promote some serious reflection for those developing our new, emerging technologies and our new products/services out there.

Who needs to be discussing/debating The Social Dilemna movie?

 

 

NVIDIA Virtual Meetings AI Tech — from theawesomer.com
With the increased need for video calls these days, those with low-bandwidth connections may experience poor video quality. This tech being developed at NVIDIA dramatically reduces bandwidth needs by sending a fixed image, then using an AI-controlled avatar to track and replicate their facial movements in real-time.

 

The pandemic pushed universities online. The change was long overdue. — from hbr-org.cdn.ampproject.org by Sean Gallagher and Jason Palmer; with thanks to Mike Mathews for his posting on LinkedIn re: this item

Excerpt:

A number of elite institutions — such as Princeton University, Williams College, Spelman College, and American University — have substantially discounted tuition for their fully online experience in an historically unprecedented fashion, highlighting pricing pressures and opening up Pandora’s box. This comes after a decade of growth in postsecondary alternatives, including “massively open online courses” (MOOCs), industry-driven certification programs, and coding bootcamps.

This moment is likely to be remembered as a critical turning point between the “time before,” when analog on-campus degree-focused learning was the default, to the “time after,” when digital, online, career-focused learning became the fulcrum of competition between institutions.

 
© 2021 | Daniel Christian