the downsides of how people use tech

Reflections on “Indian police are using facial recognition to identify protesters in Delhi” [Toussaint]

On 01/03/2020, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, ethics, future, game-changing environment, India, law schools, legislatures / government / legal, morals/values, society, the downsides of how people use tech, United States, youth, by Daniel Christian

Indian police are using facial recognition to identify protesters in Delhi — from fastcompany.com by Kristin Toussaint

Excerpt:

At Modi’s rally on December 22, Delhi police used Automated Facial Recognition System (AFRS) software—which officials there acquired in 2018 as a tool to find and identify missing children—to screen the crowd for faces that match a database of people who have attended other protests around the city, and who officials said could be disruptive.

According to the Indian Express, Delhi police have long filmed these protest events, and the department announced Monday that officials fed that footage through AFRS. Sources told the Indian news outlet that once “identifiable faces” are extracted from that footage, a dataset will point out and retain “habitual protesters” and “rowdy elements.” That dataset was put to use at Modi’s rally to keep away “miscreants who could raise slogans or banners.”

From DSC:
Here in the United States…are we paying attention to today’s emerging technologies and collaboratively working to create a future dream — versus a future nightmare!?! A vendor or organization might propose a beneficial reason to use their product or technology — and it might even meet the hype at times…but then comes along other unintended uses and consequences of that technology. For example, in the article above, what started out as a technology that was supposed to be used to find/identify missing children (a benefit) was later used to identify protesters (an unintended consequence, and a nightmare in terms of such an expanded scope of use I might add)!

Along these lines, the youth of today have every right to voice their opinions and to have a role in developing or torpedoing emerging techs. What we build and put into place now will impact their lives bigtime!

AI arms race [Burke]

On 01/03/2020, in Artificial Intelligence/Agents/LLMs/and Related, career development, change, colleges, community colleges, graphics, student-related, the downsides of how people use tech, tools, trends, United States, universities, vendors, youth, by Daniel Christian

AI arms race — insidehighered.com by Lilah Burke
More employers are using applicant tracking systems to hire employees. Some colleges are using new AI-based tools, like VMock, to help students keep up.

Excerpt:

When college students need help with their résumés, some now will be turning to algorithms rather than advisers.

In the last decade, a growing number of large companies have started hiring using applicant tracking systems, AI-based platforms that scan résumés for keywords and rank job candidates.

Similarly, video interviewing platforms that use algorithms to evaluate a candidate’s voice, gestures and emotions have become ubiquitous in some industries. HireVue, the most well-known of these platforms, has drawn accusations of being pseudoscientific and potentially exacerbating bias in hiring.

The frustration many job candidates voice when coming up against these platforms is that they have no way of knowing what they could have done better. The systems give no feedback to candidates.

So what if students, job seekers and career advisers could use the AI for themselves?

Boston University, in a document of VMock tips for students, also advised graphic design or other creative industry students to have two versions of their résumé, one with a conventional layout.

From DSC:
Per my nephew, who works in a recruiting type of position within HR for a Fortune 500 organization:

Without a doubt HR recruiting is using AI to help in the selection process.
Many companies use keyword scanners, but not everyone [and, in fact, his company did not].
HireVue is very important to use when it comes to understanding a person’s presentation skills since a lot of presenting is done via Skype/live video these days. So HireVue is not going away anytime soon. I think it’s a great system/product.
At the end of the day, a good recruiter will identify the best talent that has applied to a position. I think it’s important for students to really think about what position they’re applying for and be realistic with their applications. I think that’s where a lot of frustration happens with students that apply to positions and never get to the first round interview. They apply to 20-50 positions that don’t reflect their experience at all…so that’s where coaching and personal advisement is important

Trends to Watch in 2020

On 12/27/2019, in analytics, Artificial Intelligence/Agents/LLMs/and Related, Blockchain, career development, cloud-based computing / apps / other cloud-related, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, emerging technologies, entrepreneurship, ethics, future, health, human-computer interaction (HCI), innovation, intelligent systems, internet, law schools, legislatures / government / legal, morals/values, Natural Language Processing (NLP), pace of change, platforms, professional development, programming, the downsides of how people use tech, tools, training / L&D, trends, UK, United States, voice recognition / voice enabled interfaces, by Daniel Christian

7 Artificial Intelligence Trends to Watch in 2020 — from interestingengineering.com by Christopher McFadden

Excerpts:

Per this article, the following trends were listed:

Computer Graphics will greatly benefit from AI
Deepfakes will only get better, er, worse
Predictive text should get better and better
Ethics will become more important as time goes by
Quantum computing will supercharge AI
Facial recognition will appear in more places
AI will help in the optimization of production pipelines

Also, this article listed several more trends:

According to sources like The Next Web, some of the main AI trends for 2020 include:

The use of AI to make healthcare more accurate and less costly
Greater attention paid to explainability and trust
AI becoming less data-hungry
Improved accuracy and efficiency of neural networks
Automated AI development
Expanded use of AI in manufacturing
Geopolitical implications for the uses of AI

Artificial Intelligence offers great potential and great risks for humans in the future. While still in its infancy, it is already being employed in some interesting ways.

According to sources like Forbes, some of the next “big things” in technology include, but are not limited to:

Blockchain
Blockchain As A Service
AI-Led Automation
Machine Learning
Enterprise Content Management
AI For The Back Office
Quantum Computing AI Applications
Mainstreamed IoT

Also see:

Artificial intelligence predictions for 2020: 16 experts have their say — from verdict.co.uk by Ellen Daniel

Excerpts:

Organisations will build in processes and policies to prevent and address potential biases in AI
Deepfakes will become a serious threat to corporations
Candidate (and employee) care in the world of artificial intelligence
AI will augment humans, not replace them
Greater demand for AI understanding
Ramp up in autonomous vehicles
To fully take advantage of AI technologies, you’ll need to retrain your entire organisation
Voice technologies will infiltrate the office
IT will run itself while data acquires its own DNA
The ethics of AI
Health data and AI
AI to become an intrinsic part of robotic process automation (RPA)
BERT will open up a whole new world of deep learning use cases

The hottest trend in the industry right now is in Natural Language Processing (NLP). Over the past year, a new method called BERT (Bidirectional Encoder Representations from Transformers) has been developed for designing neural networks that work with text. Now, we suddenly have models that will understand the semantic meaning of what’s in text, going beyond the basics. This creates a lot more opportunity for deep learning to be used more widely.

Don’t trust AI until we build systems that earn trust [Marcus]

On 12/21/2019, in Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, engineering, ethics, innovation, law schools, legal technologies, legislatures / government / legal, mathematics, morals/values, platforms, society, technology (general), the downsides of how people use tech, trends, United States, by Daniel Christian

Don’t trust AI until we build systems that earn trust — from economist.com
Progress in artificial intelligence belies a lack of transparency that is vital for its adoption, says Gary Marcus, coauthor of “Rebooting AI”

Excerpts:

Mr Marcus argues that it would be foolish of society to put too much stock in today’s AI techniques since they are so prone to failures and lack the transparency that researchers need to understand how algorithms reached their conclusions.
…
As part of The Economist’s Open Future initiative, we asked Mr Marcus about why AI can’t do more, how to regulate it and what teenagers should study to remain relevant in the workplace of the future.

Trustworthy AI has to start with good engineering practices, mandated by laws and industry standards, both of which are currently largely absent. Too much of AI thus far has consisted of short-term solutions, code that gets a system to work immediately, without a critical layer of engineering guarantees that are often taken for granted in other field. The kinds of stress tests that are standard in the development of an automobile (such as crash tests and climate challenges), for example, are rarely seen in AI. AI could learn a lot from how other engineers do business.

The assumption in AI has generally been that if it works often enough to be useful, then that’s good enough, but that casual attitude is not appropriate when the stakes are high. It’s fine if autotagging people in photos turns out to be only 90 percent reliable—if it is just about personal photos that people are posting to Instagram—but it better be much more reliable when the police start using it to find suspects in surveillance photos.

120 AI predictions for 2020 — from forbes.com by Gil Press

Excerpt:

As for the universe, it is an open book for the 120 senior executives featured here, all involved with AI, delivering 2020 predictions for a wide range of topics: Autonomous vehicles, deepfakes, small data, voice and natural language processing, human and augmented intelligence, bias and explainability, edge and IoT processing, and many promising applications of artificial intelligence and machine learning technologies and tools. And there will be even more 2020 AI predictions, in a second installment to be posted here later this month.

2019 AI report tracks profound growth — from ide.mit.edu by Paula Klein

Excerpt:

Until now “we’ve been sorely lacking good data about basic questions like ‘How is the technology advancing’ and ‘What is the economic impact of AI?’ ” Brynjolfsson said. The new index, which tracks three times as many data sets as last year’s report, goes a long way toward providing answers.

…

Education

At the graduate level, AI has rapidly become the most popular specialization among computer science PhD students in North America. In 2018, over 21% of graduating Computer Science PhDs specialize in Artificial Intelligence/Machine Learning.
Industry is the largest consumer of AI talent. In 2018, over 60% of AI PhD graduates went to industry, up from 20% in 2004.
In the U.S., AI faculty leaving academia for industry continues to accelerate, with over 40 departures in 2018, up from 15 in 2012 and none in 2004.

In the U.S., #AI faculty leaving #academia for industry continues to accelerate, with over 40 departures in 2018, up from 15 in 2012 and none in 2004.

Why AI is a threat to democracy – and what we can do to stop it — from asumetech.com by Lawrence Cole

Excerpts:

In the US, however, we also have a tragic lack of foresight. Instead of creating a grand strategy for AI or for our long-term futures, the federal government has removed the financing of scientific and technical research. The money must therefore come from the private sector. But investors also expect a certain return. That is a problem. You cannot plan your R&D breakthroughs when working on fundamental technology and research. It would be great if the big tech companies had the luxury of working very hard without having to organize an annual conference to show off their newest and best whiz bang thing. Instead, we now have countless examples of bad decisions made by someone in the G-MAFIA, probably because they worked quickly. We begin to see the negative effects of the tension between doing research that is in the interest of humanity and making investors happy.
…
The problem is that our technology has become increasingly sophisticated, but our thinking about what free speech is and what a free market economy looks like has not become that advanced. We tend to resort to very basic interpretations: free speech means that all speech is free, unless it conflicts with defamation laws, and that’s the end of the story. That is not the end of the story. We need to start a more sophisticated and intelligent conversation about our current laws, our emerging technology, and how we can make the two meet halfway.

So I absolutely believe that there is a way forward. But we have to come together and bridge the gap between Silicon Valley and DC, so that we can all steer the boat in the same direction.

— Amy Webb, futurist, NYU professor, founder of the Future Today Institute

Also see:

“FRONTLINE investigates the promise and perils of artificial intelligence, from fears about work and privacy to rivalry between the U.S. and China. The documentary traces a new industrial revolution that will reshape and disrupt our lives, our jobs and our world, and allow the emergence of the surveillance society.”

The film has five distinct messages about:

1. China’s AI Plan
2. The Promise of AI
3. The Future of Work
4. Surveillance Capitalism
5. The Surveillance State

Who’s liable when a robot discriminates? [Opfer]

On 11/13/2019, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, law schools, legislatures / government / legal, platforms, robotics, society, sociology, the downsides of how people use tech, United States, workplace, by Daniel Christian

AI hiring could mean robot discrimination will head to courts — from news.bloomberglaw.com by Chris Opfer

Algorithm vendors, employers grappling with liability issues
EEOC already looking at artificial intelligence cases

Excerpt:

As companies turn to artificial intelligence for help making hiring and promotion decisions, contract negotiations between employers and vendors selling algorithms are being dominated by an untested legal question: Who’s liable when a robot discriminates?

The predictive strength of any algorithm is based at least in part on the information it is fed by human sources. That comes with concerns the technology could perpetuate existing biases, whether it is against people applying for jobs, home loans, or unemployment insurance.

From DSC:
Are law schools and their faculty/students keeping up with these kinds of issues? Are lawyers, judges, attorney generals, and others informed about these emerging technologies?

REALLY?!!! “A face-scanning algorithm increasingly decides whether you deserve the job”

On 11/06/2019, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, business, career development, ethics, law schools, legal technologies, legislatures / government / legal, morals/values, society, sociology, the downsides of how people use tech, tools, United States, vendors, by Daniel Christian

A face-scanning algorithm increasingly decides whether you deserve the job — from washingtonpost.com by Drew Harwell
HireVue claims it uses artificial intelligence to decide who’s best for a job. Outside experts call it ‘profoundly disturbing.’

Excerpt:

An artificial intelligence hiring system has become a powerful gatekeeper for some of America’s most prominent employers, reshaping how companies assess their workforce — and how prospective employees prove their worth.

Designed by the recruiting-technology firm HireVue, the system uses candidates’ computer or cellphone cameras to analyze their facial movements, word choice and speaking voice before ranking them against other applicants based on an automatically generated “employability” score.

The system, they argue, will assume a critical role in helping decide a person’s career. But they doubt it even knows what it’s looking for: Just what does the perfect employee look and sound like, anyway?

“It’s a profoundly disturbing development that we have proprietary technology that claims to differentiate between a productive worker and a worker who isn’t fit, based on their facial movements, their tone of voice, their mannerisms,” said Meredith Whittaker, a co-founder of the AI Now Institute, a research center in New York.

From DSC:
If you haven’t been screened out by an algorithm from an Applicant Tracking System recently, then you haven’t been looking for a job in the last few years. If that’s the case:

Then you might not be very interested in this posting.
You will be very surprised in the future, when you do need to search for a new job.

Because the truth is, it’s very difficult to get the eyes of a human being to even look at your resume and/or to meet you in person. The above posting/article should disturb you even more. I don’t think that the programmers have programmed everything inside an experienced HR professional’s mind.

Also see:

In case after case, courts reshape the rules around AI — from muckrock.com
AI Now Institute recommends improvements and highlights key AI litigation
Excerpt:
When undercover officers with the Jacksonville Sheriff’s Office bought crack cocaine from someone in 2015, they couldn’t actually identify the seller. Less than a year later, though, Willie Allen Lynch was sentenced to 8 years in prison, picked through a facial recognition system. He’s still fighting in court over how the technology was used, and his case and others like it could ultimately shape the use of algorithms going forward, according to a new report.

Deepfakes: When a picture is worth nothing at all [law.com]

On 11/06/2019, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, digital audio, digital video, emerging technologies, ethics, morals/values, policy, society, the downsides of how people use tech, tools, by Daniel Christian

Deepfakes: When a picture is worth nothing at all — from law.com by Katherine Forrest

Excerpt:

“Deepfakes” is the name for highly realistic, falsified imagery and sound recordings; they are digitized and personalized impersonations. Deepfakes are made by using AI-based facial and audio recognition and reconstruction technology; AI algorithms are used to predict facial movements as well as vocal sounds. In her Artificial Intelligence column, Katherine B. Forrest explores the legal issues likely to arise as deepfakes become more prevalent.

How can we stop these armies of drones from amassing?

On 10/25/2019, in 21st century, dangers of the status quo, Daniel S. Christian, emerging technologies, ideas, law schools, leadership, legislatures / government / legal, policy, technology (general), the downsides of how people use tech, trends, United States, vendors, by Daniel Christian

Drones from CVS and Walgreens are finally here—and they’re bringing Band-Aids — from fastcompany.com by Ruth Reader
With UPS and Google sister company Wing as partners, the big pharmacies are starting to deliver pills, Cheez-Its, and first-aid supplies by drone.

From DSC:
Add those drones to the following amassing armies:

Autonomous robot deliveries are coming to 100 university campuses in the U.S. — from digitaltrends.com by Luke Dormehl
Postmates Gets Go-Ahead to Test Delivery Robot in San Francisco — from interestingengineering.com by Donna Fuscaldo
Amazon patents ‘surveillance as a service’ tech for its delivery drones — from theverge.com by Jon Porter
This futuristic driverless pod will soon be delivering pizza in Texas — from digitaltrends.com by Trevor Mogg
Amazon is creating detailed 3D models of suburbia to train its new delivery robots — from theverge.com by James Vincent
‘Eventually, we’ll be delivering around the world.’

What happens when employers can read your facial expressions? — from nytimes.com by Evan Selinger and Woodrow Hartzog
The benefits do not come close to outweighing the risks.

Excerpts:

The essential and unavoidable risks of deploying these tools are becoming apparent. A majority of Americans have functionally been put in a perpetual police lineup simply for getting a driver’s license: Their D.M.V. images are turned into faceprints for government tracking with few limits. Immigration and Customs Enforcement officials are using facial recognition technology to scan state driver’s license databases without citizens’ knowing. Detroit aspires to use facial recognition for round-the-clock monitoring. Americans are losing due-process protections, and even law-abiding citizens cannot confidently engage in free association, free movement and free speech without fear of being tracked.

“Notice and choice” has been an abysmal failure. Social media companies, airlines and retailers overhype the short-term benefits of facial recognition while using unreadable privacy policies and vague disclaimers that make it hard to understand how the technology endangers users’ privacy and freedom.

From DSC:
This article illustrates how far behind the legal realm is in the United States when we look at where our society is at with wrestling with emerging technologies. Dealing with this relatively new *exponential* pace of change is very difficult for many of our institutions to deal with (higher education and the legal realm come to my mind here).

YouTube’s algorithm hacked a human vulnerability, setting a dangerous precedent — from which-50.com by Andrew Birmingham

Excerpt (emphasis DSC):

Even as YouTube’s recommendation algorithm was rolled out with great fanfare, the fuse was already burning. A project of The Google Brain and designed to optimise engagement, it did something unforeseen — and potentially dangerous.

Today, we are all living with the consequences.

As Zeynep Tufekci, an associate professor at the University of North Carolina, explained to attendees of Hitachi Vantara’s Next 2019 conference in Las Vegas this week, “What the developers did not understand at the time is that YouTube’ algorithm had discovered a human vulnerability. And it was using this [vulnerability] at scale to increase YouTube’s engagement time — without a single engineer thinking, ‘is this what we should be doing?’”

The consequence of the vulnerability — a natural human tendency to engage with edgier ideas — led to YouTube’s users being exposed to increasingly extreme content, irrespective of their preferred areas of interest.
…
“What they had done was use machine learning to increase watch time. But what the machine learning system had done was to discover a human vulnerability. And that human vulnerability is that things that are slightly edgier are more attractive and more interesting.”

From DSC:
Just because we can…

Three threats posed by deepfakes that technology won’t solve [Chen]

On 10/08/2019, in 21st century, digital audio, digital photography, digital video, law schools, leadership, legislatures / government / legal, policy, political science, society, technology (general), the downsides of how people use tech, tools, by Daniel Christian

Three threats posed by deepfakes that technology won’t solve — from technologyreview.com by Angela Chen
As deepfakes get better, companies are rushing to develop technology to detect them. But little of their potential harm will be fixed without social and legal solutions.

Excerpt:

3) Problem: Deepfake detection is too late to help victims
With deepfakes, “there’s little real recourse after that video or audio is out,” says Franks, the University of Miami scholar.

Existing laws are inadequate. Laws that punish sharing legitimate private information like medical records don’t apply to false but damaging videos. Laws against impersonation are “oddly limited,” Franks says—they focus on making it illegal to impersonate a doctor or government official. Defamation laws only address false representations that portray the subject negatively, but Franks says we should be worried about deepfakes that falsely portray people in a positive light too.

‘Goliath is winning’: The biggest U.S. banks are set to automate away 200,000 jobs — from gizmodo.com by Brian Merchant

Excerpt (excerpt):

Over the next decade, U.S. banks, which are investing $150 billion in technology annually, will use automation to eliminate 200,000 jobs, thus facilitating “the greatest transfer from labor to capital” in the industry’s history. The call is coming from inside the house this time, too—both the projection and the quote come from a recent Wells Fargo report, whose lead author, Mike Mayo, told the Financial Times that he expects the industry to shed 10 percent of all of its jobs.

This, Mayo said, will lay the groundwork for, and I quote, “a golden age of banking efficiency.” The job cuts are slated to hit front offices, call centers, and branches the hardest, where 20-30 percent of those roles will be on the chopping block. They will be replaced by better ATMs, automated chatbots, and software instruments that take advantage of big data and cloud computing to make investment decisions.

“The next decade should be the biggest decade for banks in technology in history,” Mayo said.

From DSC:
How does this impact entry level positions? How does this help a young graduate who is trying to get out of the Catch 22 with job experience? How are colleges and universities helping young people navigate these quickly changing landscapes?

Learning Ecosystems

How can we stop these armies of drones from amassing?

YouTube’s algorithm hacked a human vulnerability, setting a dangerous precedent [Birmingham]

Three threats posed by deepfakes that technology won’t solve [Chen]

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