Google and Microsoft warn that AI may do dumb things — from wired.com by Tom Simonite

Excerpt:

Alphabet likes to position itself as a leader in AI research, but it was six months behind rival Microsoft in warning investors about the technology’s ethical risks. The AI disclosure in Google’s latest filing reads like a trimmed down version of much fuller language Microsoft put in its most recent annual SEC report, filed last August:

“AI algorithms may be flawed. Datasets may be insufficient or contain biased information. Inappropriate or controversial data practices by Microsoft or others could impair the acceptance of AI solutions. These deficiencies could undermine the decisions, predictions, or analysis AI applications produce, subjecting us to competitive harm, legal liability, and brand or reputational harm.”

 

Chinese company leaves Muslim-tracking facial recognition database exposed online — from by Catalin Cimpanu
Researcher finds one of the databases used to track Uyghur Muslim population in Xinjiang.

Excerpt:

One of the facial recognition databases that the Chinese government is using to track the Uyghur Muslim population in the Xinjiang region has been left open on the internet for months, a Dutch security researcher told ZDNet.

The database belongs to a Chinese company named SenseNets, which according to its website provides video-based crowd analysis and facial recognition technology.

The user data wasn’t just benign usernames, but highly detailed and highly sensitive information that someone would usually find on an ID card, Gevers said. The researcher saw user profiles with information such as names, ID card numbers, ID card issue date, ID card expiration date, sex, nationality, home addresses, dates of birth, photos, and employer.

Some of the descriptive names associated with the “trackers” contained terms such as “mosque,” “hotel,” “police station,” “internet cafe,” “restaurant,” and other places where public cameras would normally be found.

 

From DSC:
Readers of this blog will know that I’m generally pro-technology. But especially focusing in on that last article, to me, privacy is key here. For which group of people from which nation is next? Will Country A next be tracking Christians? Will Country B be tracking people of a given sexual orientation? Will Country C be tracking people with some other characteristic?

Where does it end? Who gets to decide? What will be the costs of being tracked or being a person with whatever certain characteristic one’s government is tracking? What forums are there for combating technologies or features of technologies that we don’t like or want?

We need forums/channels for raising awareness and voting on these emerging technologies. We need informed legislators, senators, lawyers, citizens…we need new laws here…asap.

 

 

 

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.

 

 

For a next gen learning platform: A Netflix-like interface to check out potential functionalities / educationally-related “apps” [Christian]

From DSC:
In a next generation learning system, it would be sharp/beneficial to have a Netflix-like interface to check out potential functionalities that you could turn on and off (at will) — as one component of your learning ecosystem that could feature a setup located in your living room or office.

For example, put a Netflix-like interface to the apps out at eduappcenter.com (i.e., using a rolling interface at first, then going to a static page/listing of apps…again…similar to Netflix).

 

A Netflix-like interface to check out potential functionalities / educationally-related apps

 

 

 

Making New Drugs With a Dose of Artificial Intelligence — from nytimes.com by Cade Metz

Excerpt:

DeepMind specializes in “deep learning,” a type of artificial intelligence that is rapidly changing drug discovery science. A growing number of companies are applying similar methods to other parts of the long, enormously complex process that produces new medicines. These A.I. techniques can speed up many aspects of drug discovery and, in some cases, perform tasks typically handled by scientists.

“It is not that machines are going to replace chemists,” said Derek Lowe, a longtime drug discovery researcher and the author of In the Pipeline, a widely read blog dedicated to drug discovery. “It’s that the chemists who use machines will replace those that don’t.”

 

 

 

Google is bringing translation to its Home speakers — from businessinsider.com by Peter Newman

Excerpt:

Google has added real-time translation capabilities to its Google Home smart speakers, the Home Hub screened speaker, as well as other screened devices from third parties, according to Android Police.

 

Also see:

 

 

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.

 

 

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.

 

 

When the future comes to West Michigan, will we be ready?


 

UIX: When the future comes to West Michigan, will we be ready? — from rapidgrowthmedia.com by Matthew Russell

Excerpts (emphasis DSC):

“Here in the United States, if we were to personify things a bit, it’s almost like society is anxiously calling out to an older sibling (i.e., emerging technologies), ‘Heh! Wait up!!!'” Christian says. “This trend has numerous ramifications.”

Out of those ramifications, Christian names three main points that society will have to address to fully understand, make use of, and make practical, future technologies.

  1. The need for the legal/legislative side of the world to close the gap between what’s possible and what’s legal
  2. The need for lifelong learning and to reinvent oneself
  3. The need to make pulse-checking/futurism an essential tool in the toolbox of every member of the workforce today and in the future

 

When the future comes to West Michigan, will we be ready?

Photos by Adam Bird

 

From DSC:
The key thing that I was trying to relay in my contribution towards Matthew’s helpful article was that we are now on an exponential trajectory of technological change. This trend has ramifications for numerous societies around the globe, and it involves the legal realm as well. Hopefully, all of us in the workforce are coming to realize our need to be constantly pulse-checking the relevant landscapes around us. To help make that happen, each of us needs to be tapping into the appropriate “streams of content” that are relevant to our careers so that our knowledgebases are as up-to-date as possible. We’re all into lifelong learning now, right?

Along these lines, increasingly there is a need for futurism to hit the mainstream. That is, when the world is moving at 120+mph, the skills and methods that futurists follow must be better taught and understood, or many people will be broadsided by the changes brought about by emerging technologies. We need to better pulse-check the relevant landscapes, anticipate the oncoming changes, develop potential scenarios, and then design the strategies to respond to those potential scenarios.

 

 

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