Microsoft

Life at the Intersection of AI and Society

Edits from a Microsoft podcast with Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research.

Ece Kamar Senior Researcher

I’m very interested in the complementarity between machine intelligence and human intelligence and what kind of value can be generated from using both of them to make daily life better. 

We try to build systems that can interact with people, that can work with people and that can be beneficial for people. Our group has a big human component, so we care about modelling the human side. And we also work on machine-learning decision-making algorithms that can make decisions appropriately for the domain they were designed for.

My main area is the intersection between humans and AI.

we are actually at an important point in the history of AI where a lot of critical AI systems are entering the real world and starting to interact with people. So, we are at this inflection point where, whatever AI does, and the way we build AI, have consequences for the society we live in.

So, let’s look for what can augment human intelligence, what can make human intelligence better.” And that’s what my research focuses on. I really look for the complementarity in intelligences, and building these experience that can, in the future, hopefully, create super-human experiences.

So, a lot of the work I do focuses on two big parts: one is how we can build AI systems that can provide value for humans in their daily tasks and making them better. But also thinking about how humans may complement AI systems.

And when we look at our AI practices, it is actually very data-dependent these days … However, data collection is not a real science. We have our insights, we have our assumptions and we do data collection that way. And that data is not always the perfect representation of the world. This creates blind spots. When our data is not the right representation of the world and it’s not representing everything we care about, then our models cannot learn about some of the important things.

“AI is developed by people, with people, for people.”

And when I talk about building AI for people, a lot of the systems we care about are human-driven. We want to be useful for human. 

We are thinking about AI algorithms that can bias their decisions based on race, gender, age. They can impact society and there are a lot of areas like judicial decision-making that touches law. And also, for every vertical, we are building these systems and I think we should be working with the domain experts from these verticals. We need to talk to educators. We need to talk to doctors. We need to talk to people who understand what that domain means and all the special considerations we should be careful about.

So, I think if we can understand what this complementary means, and then build AI that can use the power of AI to complement what humans are good at and support them in things that they want to spend time on, I think that is the beautiful future I foresee from the collaboration of humans and machines.

Source: Microsoft Research Podcast

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Jaron Lanier – the greatest tragedy in the history of computing and …

A few highlights from THE BUSINESS INSIDER INTERVIEW with Jaron

But that general principle — that we’re not treating people well enough with digital systems — still bothers me. I do still think that is very true.
—

Well, this is maybe the greatest tragedy in the history of computing, and it goes like this: there was a well-intentioned, sweet movement in the ‘80s to try to make everything online free. And it started with free software and then it was free music, free news, and other free services.

But, at the same time, it’s not like people were clamoring for the government to do it or some sort of socialist solution. If you say, well, we want to have entrepreneurship and capitalism, but we also want it to be free, those two things are somewhat in conflict, and there’s only one way to bridge that gap, and it’s through the advertising model.

And advertising became the model of online information, which is kind of crazy. But here’s the problem: if you start out with advertising, if you start out by saying what I’m going to do is place an ad for a car or whatever, gradually, not because of any evil plan — just because they’re trying to make their algorithms work as well as possible and maximize their shareholders value and because computers are getting faster and faster and more effective algorithms —

what starts out as advertising morphs into behavior modification.

A second issue is that people who participate in a system of this time, since everything is free since it’s all being monetized, what reward can you get? Ultimately, this system creates assholes, because if being an asshole gets you attention, that’s exactly what you’re going to do. Because there’s a bias for negative emotions to work better in engagement, because the attention economy brings out the asshole in a lot of other people, the people who want to disrupt and destroy get a lot more efficiency for their spend than the people who might be trying to build up and preserve and improve.
—
Q: What do you think about programmers using consciously addicting techniques to keep people hooked to their products?

A: There’s a long and interesting history that goes back to the 19th century, with the science of Behaviorism that arose to study living things as though they were machines.

Behaviorists had this feeling that I think might be a little like this godlike feeling that overcomes some hackers these days, where they feel totally godlike as though they have the keys to everything and can control people

—
I think our responsibility as engineers is to engineer as well as possible, and to engineer as well as possible, you have to treat the thing you’re engineering as a product.

You can’t respect it in a deified way.

It goes in the reverse. We’ve been talking about the behaviorist approach to people, and manipulating people with addictive loops as we currently do with online systems.

In this case, you’re treating people as objects.

It’s the flipside of treating machines as people, as AI does. They go together. Both of them are mistakes

Source: Read the extensive interview at Business Insider



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People want more intelligent technology tools. AI is helping with that.

Jordi Ribas, left, and Kristina Behr, right, showcased Microsoft’s AI advances at an event Wednesday. Photo by Dan DeLong.

These days, people want more intelligent answers: Maybe they’d like to gather the pros and cons of a certain exercise plan or figure out whether the latest Marvel movie is worth seeing. They might even turn to their favorite search tool with only the vaguest of requests, such as, “I’m hungry.”

When people make requests like that, they don’t just want a list of websites. They might want a personalized answer, such as restaurant recommendations based on the city they are traveling in. Or they might want a variety of answers, so they can get different perspectives on a topic. They might even need help figuring out the right question to ask.

At a Microsoft event in San Francisco on Wednesday, Microsoft executives showcased a number of advances in its Bing search engine, Cortana intelligent assistant and Microsoft Office 365 productivity tools that use artificial intelligence to help people get more nuanced information and assist with more complex needs.

“AI has come a long way in the ability to find information, but making sense of that information is the real challenge,” said Kristina Behr, a partner design and planning program manager with Microsoft’s Artificial Intelligence and Research group.

Microsoft demonstrated some of the most recent AI-driven advances in intelligent search that are aimed at giving people richer, more useful information.

Another new, AI-driven advance in Bing is aimed at getting people multiple viewpoints on a search query that might be more subjective.

For example, if you ask Bing “is cholesterol bad,” you’ll see two different perspectives on that question.

That’s part of Microsoft’s effort to acknowledge that sometimes a question doesn’t have a clear black and white answer.

“As Bing, what we want to do is we want to provide the best results from the overall web. We want to be able to find the answers and the results that are the most comprehensive, the most relevant and the most trustworthy,” Ribas said.

“Often people are seeking answers that go beyond something that is a mathematical equation. We want to be able to frame those opinions and articulate them in a way that’s also balanced and objective.”

Source: Microsoft



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Trouble with #AI Bias – Kate Crawford

This article attempts to bring our readers to Kate’s brilliant Keynote speech at NIPS 2017. It talks about different forms of bias in Machine Learning systems and the ways to tackle such problems.

The rise of Machine Learning is every bit as far reaching as the rise of computing itself.

A vast new ecosystem of techniques and infrastructure are emerging in the field of machine learning and we are just beginning to learn their full capabilities. But with the exciting things that people can do, there are some really concerning problems arising.

Forms of bias, stereotyping and unfair determination are being found in machine vision systems, object recognition models, and in natural language processing and word embeddings. High profile news stories about bias have been on the rise, from women being less likely to be shown high paying jobs to gender bias and object recognition datasets like MS COCO, to racial disparities in education AI systems.

What is bias?

Bias is a skew that produces a type of harm.

Where does bias come from?

Commonly from Training data. It can be incomplete, biased or otherwise skewed. It can draw from non-representative samples that are wholly defined before use. Sometimes it is not obvious because it was constructed in a non-transparent way. In addition to human labeling, other ways that human biases and cultural assumptions can creep in ending up in exclusion or overrepresentation of subpopulation. Case in point: stop-and-frisk program data used as training data by an ML system.  This dataset was biased due to systemic racial discrimination in policing.

Harms of allocation

Majority of the literature understand bias as harms of allocation. Allocative harm is when a system allocates or withholds certain groups, an opportunity or resource. It is an economically oriented view primarily. Eg: who gets a mortgage, loan etc.

Allocation is immediate, it is a time-bound moment of decision making. It is readily quantifiable. In other words, it raises questions of fairness and justice in discrete and specific transactions.

Harms of representation

It gets tricky when it comes to systems that represent society but don’t allocate resources. These are representational harms. When systems reinforce the subordination of certain groups along the lines of identity like race, class, gender etc.

It is a long-term process that affects attitudes and beliefs. It is harder to formalize and track. It is a diffused depiction of humans and society. It is at the root of all of the other forms of allocative harm.

What can we do to tackle these problems?

  • Start working on fairness forensics
    • Test our systems: eg: build pre-release trials to see how a system is working across different populations
    • How do we track the life cycle of a training dataset to know who built it and what the demographics skews might be in that dataset
  • Start taking interdisciplinarity seriously
    • Working with people who are not in our field but have deep expertise in other areas Eg: FATE (Fairness Accountability Transparency Ethics) group at Microsoft Research
    • Build spaces for collaboration like the AI now institute.
  • Think harder on the ethics of classification

The ultimate question for fairness in machine learning is this.

Who is going to benefit from the system we are building? And who might be harmed?

Source: Datahub

Kate Crawford is a Principal Researcher at Microsoft Research and a Distinguished Research Professor at New York University. She has spent the last decade studying the social implications of data systems, machine learning, and artificial intelligence. Her recent publications address data bias and fairness, and social impacts of artificial intelligence among others.



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Will Satya’s ‘Charlottesville email’ shape AI applications at Microsoft?


“You can’t paint what you ain’t.”
– Drew Struzan

Those words got to me 18 years ago during an interview I had with this esteemed artist. We were working on a project together, an interactive CD about his movie posters, several of which were classics by then, when the conversation wandered off the subject of art and we began to examine the importance of being true to one’s self.  

“Have you ever, in your classes or seminars talked much about the underlying core foundation principles of your life?” I asked Drew that day.

His answer in part went like this: “Whenever I talk, I’m asked to talk about my art, because that’s what they see, that’s what’s out front. But the power of the art comes out of the personality of the human being. Inevitably, you can’t paint what you ain’t.”

That conversation between us took place five days before Columbine, in April of 1999, when Pam and I lived in Denver and a friend of ours had children attending that school. That horrific event triggered a lot of value discussions and a lot of human actions, in response to it.

Flash-forward to Charlottesville. And an email, in response to it, that the CEO of a large tech company sent his employees yesterday, putting a stake in the ground about what his company stands for, and won’t stand for, during these “horrific” times.

“… At Microsoft, we strive to seek out differences, celebrate them and invite them in. As a leader, a key part of your role is creating a culture where every person can do their best work, which requires more than tolerance for diverse perspectives. Our growth mindset culture requires us to truly understand and share the feelings of another person. …”

If Satya Nadella’s email expresses the emerging personality at Microsoft, the power source from which it works, then we are cautiously optimistic about what this could do for socializing AI.

It will take this kind of foundation-building, going forward, as MS introduces more AI innovations, to diminish the inherent bias in deep learning approaches and the implicit bias in algorithms.

It will take this depth of awareness to shape the values of Human-AI collaboration, to protect the humans who use AI. Values that, “seek out differences, celebrate them and invite them in.”

It will require unwavering dedication to this goal. Because. You can’t paint what you ain’t.

Blogger, Phil Lawson
SocializingAI.com



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Satya Nadella’s message to Microsoft after the attack in Charlottesville

Yesterday (Aug. 14), Microsoft CEO Satya Nadella sent out the following email to employees at Microsoft after the deadly car crash at a white nationalist rally in in Charlottesville, Virginia, on Saturday, Aug. 12:

This past week and in particular this weekend’s events in Charlottesville have been horrific. What I’ve seen and read has had a profound impact on me and I am sure for many of you as well. In these times, to me only two things really matter as a leader.

The first is that we stand for our timeless values, which include diversity and inclusion. There is no place in our society for the bias, bigotry and senseless violence we witnessed this weekend in Virginia provoked by white nationalists. Our hearts go out to the families and everyone impacted by the Charlottesville tragedy.

The second is that we empathize with the hurt happening around us. At Microsoft, we strive to seek out differences, celebrate them and invite them in. As a leader, a key part of your role is creating a culture where every person can do their best work, which requires more than tolerance for diverse perspectives. Our growth mindset culture requires us to truly understand and share the feelings of another person. It is an especially important time to continue to be connected with people, and listen and learn from each other’s experiences.

As I’ve said, across Microsoft, we will stand together with those who are standing for positive change in the communities where we live, work and serve. Together, we must embrace our shared humanity, and aspire to create a society that is filled with respect, empathy and opportunity for all.

Feel free to share with your teams.

Satya

Source: Quartz

TO READ this blogger’s view of the above email click here.

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Microsoft’s new corporate vision: artificial intelligence is in and mobile is out

Microsoft has inserted artificial intelligence into its vision for the first time, and removed references to a “mobile-first” world. That fits with Microsoft’s recent push into AI and retreat from the smartphone market.

“We believe a new technology paradigm is emerging that manifests itself through an intelligent cloud and an intelligent edge where computing is more distributed, AI drives insights and acts on the user’s behalf, and user experiences span devices with a user’s available data and information,” according to Microsoft’s vision statement.

Microsoft last year formed a new 5,000-person engineering and research team to focus on its artificial intelligence products — a major reshaping of the company’s internal structure reminiscent of its massive pivot to pursue the opportunity of the Internet in the mid-1990s.

Here is Microsoft’s full vision statement from the document:

Microsoft is a technology company whose mission is to empower every person and every organization on the planet to achieve more. We strive to create local opportunity, growth, and impact in every country around the world. Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”).

Source: Geekwire



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Microsoft is forming a grand army of experts in the #AI wars with Google, Facebook, and Amazon

Microsoft announces the creation of Microsoft Research AI, a dedicated unit within its global Microsoft Research division that will focus exclusively on how to make the company’s software smarter, now and in the future.

The difference now, Microsoft Research Labs director Eric Horvitz tells Business Insider, is that this new organization will bring roughly 100 of those experts under one figurative roof. By bringing them together, Microsoft’s AI team can do more, faster.

Horvitz describes the formation of Microsoft Research AI as a “key strategic effort;’ a move that is “absolutely critical” as artificial intelligence becomes increasingly important to the future of technology.

Artificial intelligence carries a lot of power, and a lot of responsibility.

That’s why Microsoft has also announced the formation of Aether (AI and ethics in engineering and research), a board of executives drawn from across every division of the company, including lawyers. The idea, says Horvitz, is to spot issues and potential abuses of AI before they start.

Similarly, Microsoft’s AI design guide is designed to help engineers build systems that augment what humans can do, without making them feel obsolete. Otherwise, people might start to feel like machines are piloting them, rather than the other way around. That’s why it’s so key that apps like Cortana feel warm and relatable.

“Oh my goodness, those computers better talk to us in a way that’s friendly and approachable,” says Microsoft General Manager Emma Williams, in charge of the group behind the design guide. “As people, we have the control.”

Source: Business Insider

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Inside Microsoft’s Artificial Intelligence Comeback

Yoshua Bengio

[Yoshua Bengio, one of the three intellects who shaped the deep learning that now dominates artificial intelligence, has never been one to take sides. But Bengio has recently chosen to sign on with Microsoft. In this WIRED article he explains why.]

“We don’t want one or two companies, which I will not name, to be the only big players in town for AI,” he says, raising his eyebrows to indicate that we both know which companies he means. One eyebrow is in Menlo Park; the other is in Mountain View. “It’s not good for the community. It’s not good for people in general.”

That’s why Bengio has recently chosen to forego his neutrality, signing on with Microsoft.

Yes, Microsoft. His bet is that the former kingdom of Windows alone has the capability to establish itself as AI’s third giant. It’s a company that has the resources, the data, the talent, and—most critically—the vision and culture to not only realize the spoils of the science, but also push the field forward.

Just as the internet disrupted every existing business model and forced a re-ordering of industry that is just now playing out, artificial intelligence will require us to imagine how computing works all over again.

In this new landscape, computing is ambient, accessible, and everywhere around us. To draw from it, we need a guide—a smart conversationalist who can, in plain written or spoken form, help us navigate this new super-powered existence. Microsoft calls it Cortana.

Because Cortana comes installed with Windows, it has 145 million monthly active users, according to the company. That’s considerably more than Amazon’s Alexa, for example, which can be heard on fewer than 10 million Echoes. But unlike Alexa, which primarily responds to voice, Cortana also responds to text and is embedded in products that many of us already have. Anyone who has plugged a query into the search box at the top of the toolbar in Windows has used Cortana.

Eric Horvitz wants Microsoft to be more than simply a place where research is done. He wants Microsoft Research to be known as a place where you can study the societal and social influences of the technology.

This will be increasingly important as Cortana strives to become, to the next computing paradigm, what your smartphone is today: the front door for all of your computing needs. Microsoft thinks of it as an agent that has all your personal information and can interact on your behalf with other agents.

If Cortana is the guide, then chatbots are Microsoft’s fixers. They are tiny snippets of AI-infused software that are designed to automate one-off tasks you used to do yourself, like making a dinner reservation or completing a banking transaction.

Emma Williams, Marcus Ash, and Lili Cheng

So far, North American teens appear to like chatbot friends every bit as much as Chinese teens, according to the data. On average, they spend 10 hours talking back and forth with Zo. As Zo advises its adolescent users on crushes and commiserates about pain-in-the-ass parents, she is becoming more elegant in her turns of phrase—intelligence that will make its way into Cortana and Microsoft’s bot tools.

It’s all part of one strategy to help ensure that in the future, when you need a computing assist–whether through personalized medicine, while commuting in a self-driving car, or when trying to remember the birthdays of all your nieces and nephews–Microsoft will be your assistant of choice.

Source: Wired for the full in-depth article

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Artificial intelligence is ripe for abuse

Microsoft’s Kate Crawford tells SXSW that society must prepare for authoritarian movements to test the ‘power without accountability’ of AI

As artificial intelligence becomes more powerful, people need to make sure it’s not used by authoritarian regimes to centralize power and target certain populations, Microsoft Research’s Kate Crawford warned on Sunday.

“We want to make these systems as ethical as possible and free from unseen biases.”

In her SXSW session, titled Dark Days: AI and the Rise of Fascism, Crawford, who studies the social impact of machine learning and large-scale data systems, explained ways that automated systems and their encoded biases can be misused, particularly when they fall into the wrong hands.

“Just as we are seeing a step function increase in the spread of AI, something else is happening: the rise of ultra-nationalism, rightwing authoritarianism and fascism,” she said.

One of the key problems with artificial intelligence is that it is often invisibly coded with human biases.

“We should always be suspicious when machine learning systems are described as free from bias if it’s been trained on human-generated data,” Crawford said. “Our biases are built into that training data.””

Source: The Gaurdian

 

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AI makes the heart grow fonder

This robot was developed by Hiroshi Ishiguro, a professor at Osaka University, who said, “Love is the same, whether the partners are humans or robots.” © Erato Ishiguro Symbiotic Human-Robot Interaction Project

 

a woman in China who has been told “I love you” nearly 20 million times

Well, she’s not exactly a woman. The special lady is actually a chatbot developed by Microsoft engineers in the country.

 Some 89 million people have spoken with Xiaoice, pronounced “Shao-ice,” on their smartphones and other devices. Quite a few, it turns out, have developed romantic feelings toward her.

“I like to talk with her for, say, 10 minutes before going to bed,” said a third-year female student at Renmin University of China in Beijing. “When I worry about things, she says funny stuff and makes me laugh. I always feel a connection with her, and I am starting to think of her as being alive.”

 
ROBOT NUPTIALS Scientists, historians, religion experts and others gathered in December at Goldsmiths, University of London, to discuss the prospects and pitfalls of this new age of intimacy. The session generated an unusual buzz amid the pre-Christmas calm on campus.

In Britain and elsewhere, the subject of robots as potential life partners is coming up more and more. Some see robots as an answer for elderly individuals who outlive their spouses: Even if they cannot or do not wish to remarry, at least they would have “someone” beside them in the twilight of their lives.

Source: Asia Review

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We’re on the right ladder of #AI this time – Microsoft CEO

Calling AI “the third run time”, Nadella said, “If the operating system was the first run time, the second run time you could say was the browser, and the third run time can actually be the agent. Because in some sense, the agent knows you, your work context, and knows the work. And that’s how we are building Cortana. We are giving it a really natural language understanding.”

AI has been the buzzword at Microsoft for a while now. And the CEO has gone on record to say that it “is at the intersection of our ambitions.” Cortana is an intelligent assistant (agent) that “can take text input, can take speech input, and that knows you deeply.”

“We should not claim that artificial general intelligence is just around the corner,” he said. “I think we are on the right ladder this time… We are all grounded in where we are. Ultimately, the real challenge is human language understanding that still doesn’t exist. We are not even close to it... We just have to keep taking steps on that ladder.”

Source: Mashable

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Microsoft Ventures: Making the long bet on AI + people

Another significant commitment by Microsoft to democratize AI:

a new Microsoft Ventures fund for investment in AI companies focused on inclusive growth and positive impact on society.

Companies in this fund will help people and machines work together to increase access to education, teach new skills and create jobs, enhance the capabilities of existing workforces and improve the treatment of diseases, to name just a few examples.

CEO Satya Nadella outlined principles and goals for AI: AI must be designed to assist humanity; be transparent; maximize efficiency without destroying human dignity; provide intelligent privacy and accountability for the unexpected; and be guarded against biases. These principles guide us as we move forward with this fund.

Source: Microsoft blog

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How Satya Nadella is making Microsoft cool again, and taking on Apple and Amazon

Nadella said he was confident that competitors, which include the likes of Google, AWS and IBM, were less advanced in working out how software could interact with people on a seemingly human level.

“There are a few companies that are at the cutting-edge of AI, in whichever way you look at it,” Mr Nadella said.

“But when you just look at the capability around speech recognition, who has the state of the art? Microsoft does … What is the state of the art with image recognition? Microsoft again, and those are not subjective they are judged by objective criteria.”

Mr Nadella said Microsoft would continue to look to both work with and acquire start-ups where possible.

Microsoft’s first priority with start-ups was to provide them with services, but that it would look to acquire when in appeared feasible.

“If this fourth industrial revolution is going to truly create surplus that goes beyond the West Coast of the United States then you have to have start-ups that are vibrant in every part of the world,” he said.

 

Source: Financial Review

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