Category Archives: Artificial Intelligence

The Libertarian Republic

Artificial Intelligence Is A Government Program The Libertarian Republic Like welfare, green technology, and Katy Perry, artificial intelligence is a government program. But what exactly does that mean? Essentially, taxpayer money is funneled into the hands of a select group of corporatists, thus protecting them from the ...

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Artificial Intelligence Is A Government Program - The Libertarian Republic

To get computers to think like humans, we need a new A.I. paradigm, one that places top down and bottom up knowledge on equal footing. Bottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling on our retina. Top-down knowledge comprises cognitive models of the world and how it works.

Deep learning is very good at bottom-up knowledge, like discerning which patterns of pixels correspond to golden retrievers as opposed to Labradors. But it is no use when it comes to top-down knowledge. If my daughter sees her reflection in a bowl of water, she knows the image is illusory; she knows she is not actually in the bowl. To a deep-learning system, though, there is no difference between the reflection and the real thing, because the system lacks a theory of the world and how it works. Integrating that sort of knowledge of the world may be the next great hurdle in A.I., a prerequisite to grander projects like using A.I. to advance medicine and scientific understanding.

I fear, however, that neither of our two current approaches to funding A.I. research small research labs in the academy and significantly larger labs in private industry is poised to succeed. I say this as someone who has experience with both models, having worked on A.I. both as an academic researcher and as the founder of a start-up company, Geometric Intelligence, which was recently acquired by Uber.

Academic labs are too small. Take the development of automated machine reading, which is a key to building any truly intelligent system. Too many separate components are needed for any one lab to tackle the problem. A full solution will incorporate advances in natural language processing (e.g., parsing sentences into words and phrases), knowledge representation (e.g., integrating the content of sentences with other sources of knowledge) and inference (reconstructing what is implied but not written). Each of those problems represents a lifetime of work for any single university lab.

Corporate labs like those of Google and Facebook have the resources to tackle big questions, but in a world of quarterly reports and bottom lines, they tend to concentrate on narrow problems like optimizing advertisement placement or automatically screening videos for offensive content. There is nothing wrong with such research, but it is unlikely to lead to major breakthroughs. Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesnt understand a word of what it is translating.

I look with envy at my peers in high-energy physics, and in particular at CERN, the European Organization for Nuclear Research, a huge, international collaboration, with thousands of scientists and billions of dollars of funding. They pursue ambitious, tightly defined projects (like using the Large Hadron Collider to discover the Higgs boson) and share their results with the world, rather than restricting them to a single country or corporation. Even the largest open efforts at A.I., like OpenAI, which has about 50 staff members and is sponsored in part by Elon Musk, is tiny by comparison.

An international A.I. mission focused on teaching machines to read could genuinely change the world for the better the more so if it made A.I. a public good, rather than the property of a privileged few.

Gary Marcus is a professor of psychology and neural science at New York University.

Follow The New York Times Opinion section on Facebook and Twitter (@NYTopinion), and sign up for the Opinion Today newsletter.

A version of this op-ed appears in print on July 30, 2017, on Page SR6 of the New York edition with the headline: A.I. Is Stuck. Lets Unstick It.

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Artificial Intelligence Is Stuck. Here's How to Move It Forward. - New York Times

Forget Donald Trump. Lets talk about something truly dim and oafish: emoji.

The world is in the middle of a disturbing emoji-gasm. You can go see The Emoji Movie and sit through a plot as nuanced and complex as an old episode of Mister Rogers Neighborhood. (Dont miss esteemed Shakespearean actor Patrick Stewart getting to be the voice of Poop.) July also brought us World Emoji Day. To mark the occasion, Apple trumpeted its upcoming release of new emoji, a milestone for society that might only be topped by a new shape of marshmallow in Lucky Charms. Microsoft, always an innovator in artificial intelligence, announced a version of its SwiftKey phone keyboard that will predict which emoji you should use based on what youre typing. Just one more reason to be scared of AI.

Billions of emoji fly around the planet every daythose tiny cartoons of faces and things that supposedly let us express ourselves in ways words cant, unless you know a lot of words. Emoji are such a rage, they have to be governed by a global nonprofit called the Unicode Consortiumkind of like the G-20 for smiley faces. Full members include companies such as Apple, Google, Huawei, SAP and IBM. The group has officially sanctioned 2,666 emoji that can be used across any technology platform. Obviously, the people who sit on the Unicode board do important work. This is why the middle finger emoji you type on your iPhone can look the same on an SAP-generated corporate financial report.

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Emoji are displayed on the Touch Bar on a new Apple MacBook Pro laptop during a product launch event on October 27, 2016 in Cupertino, California. Stephen Lam/Getty

Maybe I dont get emoji because Im a guy. At least thats what Cosmopolitan suggests in a story headlined, Why Your Boyfriend Hates Emoji: Dont blame him, he cant help it. The story explains: Straight guys aren't conditioned to flash bashful smiles. They don't do cute winks. They don't make a cute kissy face. Then again, the articles male writer might not be the most enlightened about gender roles in the 21st century. Another Cosmo story by the same person is headlined, 13 Things Guys Secretly Want to Do With Your Boobs.

Still, serious academics seem to think emoji are serious. (Oh, and I consider the word emoji to be both singular and plural. The kind of people who say emojis are the kind of people who say shrimps.) Researchers from the University of Michigan and Peking University analyzed 427 million emoji-laden messages from 212 countries to understand how emoji use differs across the globe. Those passionate French are the heaviest emoji users. Mexicans send the most negative emojiyet another justification for keeping them behind a wall. Or you can read The Semiotics of Emoji, by Marcel Danesi, an anthropologist at the University of Toronto. The emoji code harbors within it many implications for the future of writing, literacy, and even human consciousness, he writes. Whoa, dude! Someday, we might think in emoji! Hold on while I fire up my Pax and let my mind be blown.

Much of the emoji trend can be blamed on the Japanese, fervent purveyors of creepy-cute characters like Hello Kitty and Pikachu. In the 1990s, when Japan was the smartest player in electronics, NTT DoCoMo introduced the first sort-of-smartphone service called i-mode. Shigetaka Kurita, part of the i-mode team, recalled being disappointed by weather reports that just sent the word fine to his phone instead of showing a smiling, shining sun like he saw on TV. That gave him the idea of creating tiny symbols for i-mode. The first batch of 176 was inspired by facial expressions, street signs and symbols used in manga. The word emoji comes from a mashup of the Japanese words for picture and character.

The rest of the blame for this trend falls on Apple. After introducing the iPhone in 2007, Apple wanted to break into the Japanese market, where users had by then grown accustomed to emoji. So it had to include emoji on the iPhone. That led to people in other countries finding and using the emoji on their iPhones, spreading these things like lice. As emoji got more popular, users wanted more kinds for all kinds of devices. Companies such as Apple and Google keep creating new emoji and proposing them to the Unicode Consortium, which is how weve gotten so many odd emoji, like a roller coaster, cactus, pickax and the eggplantwhich, if you dont know your emoji, you shouldnt send to your mother.

The question now is: What does emoji-mania mean? There are those, like Danesi, who believe were inventing a new language based on pictogramssomething like Chinese, except with no spoken version of the symbols. Generations from now, people will ride in driverless flying Ubers and communicate with one another in nothing but emoji. Novels will be written in emoji. (An engineer, Fred Benenson, already translated Moby-Dick into emoji. Call me Ishmael is a phone, a mans face, a sailboat, a whale and a hand doing an OK sign.)

That vision of the future, though, ignores an important trend. As Amazons Alexa and similar services are showing, AI software is going to get really good at communicating with us by voice. Were going to stop relying so much on typing with our thumbs and looking at screens. Well converse with the technology and one another. Then, the fact that you cant speak in emoji might actually be the end of the damn things. In another decade, we could look back at emoji as a peculiar artifact of an era, like 10-4, good buddy chatter during the 1970s citizens band radio craze.

Then again, emoji might be another sign of the growing anti-intellectual, anti-science movement in America. Maybe emoji are, in fact, where language and thinking are headingaway from the precision of words and toward the primitive grunts of cartoon images. The nation has already elected a president who writes only in tweets. If he wins another term, he might go another level lower, thrilling supporters by communicating his foreign policy position in nothing but a Russian flag, hearts and an eggplant.

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Emojis Are Everywhere, But For How Long? Artificial Intelligence Could Soon Replace Our Smiley Face Friends - Newsweek

If we're going to create software that can think and speak for itself, we should at least know what it's saying. Right?

That was the conclusion reached by Facebook researchers who recently developed a sophisticated negotiation software that started off speaking English. Two artificial intelligence agents, however, began conversing in their own shorthand that appeared to be gibberish but was perfectly coherent to themselves.

A sample of their conversation:

Bob: I can can I I everything else.

Alice: Balls have zero to me to me to me to me to me to me to me to me to.

Dhruv Batra, a Georgia Tech researcher at Facebook's AI Research (FAIR), told Fast Co. Design "there was no reward" for the agents to stick to English as we know it, and the phenomenon has occurred multiple times before. It is more efficient for the bots, but it becomes difficult for developers to improve and work with the software.

"Agents will drift off understandable language and invent codewords for themselves," Batra said. Like if I say 'the' five times, you interpret that to mean I want five copies of this item. This isnt so different from the way communities of humans create shorthands."

Convenient as it may have been for the bots, Facebook decided to require the AI to speak in understandable English.

"Our interest was having bots who could talk to people," FAIR scientist Mike Lewis said.

In a June 14 post describing the project, FAIR researchers said the project "represents an important step for the research community and bot developers toward creating chatbots that can reason, converse, and negotiate, all key steps in building a personalized digital assistant."

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Artificial intelligence system makes its own language, researchers pull the plug - WESH Orlando

NEW DELHI: When it comes to delivering intelligent Cloud experience, robust artificial intelligence (AI)-driven solutions are going to decide who is better equipped to provide enterprises with extended capabilities, says a key IBM executive.

Among all future technologies, AI has been hailed as the next big thing and is steadily becoming the driving force behind tech innovations and existing product lines across industries -- going further from just being part of Internet of Things (IoT)-enabled home appliances and smartphones.

Market research firm Tractica forecasts that the revenue generated from the direct and indirect application of AI software will grow from $1.38 billion in 2016 to $59.75 billion by 2025. According to IDC, the cognitive systems and AI market (including hardware and services) will grow to $47 billion in 2020.

To make sense of data on Cloud, data miners need to decode and align it in order to deliver enhanced experiences to customers and they can't do this mammoth task alone.

Here is where AI -- their "virtual colleagues" -- steps in to help them deliver "enterprise-grade" Cloud that scales to the requirements of the market and benefits all industries.

"When I say an 'enterprise-grade' Cloud, I mean that we have a global network of data centres. We have about 252 data centres worldwide, offering a full range of services that includes virtualised infrastructure," Vikas Arora, Country Manager, Cloud Business, IBM India and South Asia, told IANS.

Present in India since 1951, IBM India has expanded its operations with regional headquarters in Bengaluru and offices across 20 cities.

IBM has research centres in Delhi and Bengaluru; software labs in Bengaluru, Gurgaon, Pune, Hyderabad and Mumbai; India Systems Development Labs (ISDL) in Bengaluru, Pune and Hyderabad; a Cloud data centre in Chennai; and eight delivery centres across the country.

With over 55 Cloud centres in 19 countries, IBM Cloud is the leader in Enterprise Cloud. IBM's $14.6 billion cloud business grew 35 per cent in the first quarter this year.

With a market capitalisation of over $135 billion, IBM, which traditionally has been manufacturing and selling computer hardware and software, has now forayed into areas like AI and cognitive analytics.

The company now provides tools for data management that are able to analyse the data -- be it on public or private Cloud -- so as to translate it into useful insights.

"What makes us different is that our Cloud is built for the cognitive era. There are many robust artificial intelligence capabilities with us, led by 'IBM Watson'," Arora told IANS.

IBM Watson is an intelligent cognitive system. With it, people can analyse and interpret data, including unstructured text, images, audio and video, and develop personalised solutions.

Watson now has a new cognitive assistant, the "MaaS360 Advisor" that leverages its capabilities to help IT professionals effectively manage and protect networks of smartphones, tablets, laptops, IoT devices and other endpoints.

"We believe that at some point, everyone would be able to provide Cloud; but I think the solutions that are going to win are those that are able to provide customers with extended capabilities, which they are going to need for the future and AI is a big part of that," Arora noted.

When it comes to the Indian Cloud ecosystem, CTOs and CEOs want to control their data on-premises.

"I think it's not as much about control. It is basically about trying to get the most out of whatever investments have already been made. So we don't see control other than, of course, in industries that are heavily regulated where they need control," Arora explained.

More than control, added the IBM executive, it's efficiency and return-on-investments that drive large enterprises -- but it is different for mid-sized organisations.

"For them, it's more about reducing the headache of handling an IT department, building an infrastructure and having someone managing it. Mid-sized organisations tend to struggle on this point as this isn't their core business," Arora said.

When it comes to working with the government in the country, IBM sees a positive trend emerging. "Today, government departments have a clear set of guidelines as to what a Cloud environment should deliver in terms of capabilities, operational management, security and sovereignty," the IBM executive maintained.

Among Small and Medium Enterprises (SMEs), new IT spend is giving Cloud a big push.

"SMEs are not hesitant any longer to go for New-Age IT initiatives because they are not relying on a hardware vendor or a small system integrator and aim to have a world-class IT environment in Cloud, without having to have a particular IT department around it," Arora told IANS.

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Artificial Intelligence-enabled Cloud solutions set to win the race: IBM India - Economic Times

Have you ever wanted to sit and drift through a magical world? Disney Research has developed a Magic Bench platform that actualises this dream by combining augmented reality (AR) and mixed reality experience.

In this platform, wearing a head-mounted display or using a handheld device is not required. Instead, the surroundings are instrumented rather than the individual, allowing people to share the magical experience as a group.Moshe Mahler, Principal Digital Artist at Disney Research, said,

This platform creates a multi-sensory immersive experience in which a group can interact directly with an animated character. Our mantra for this project washear a character coming, see them enter the space, and feel them sit next to you.

The Magic Bench shows people their mirrored images on a large screen in front of them, creating a third person point of view. In a paper that will be presented at SIGGRAPH 2017 event in Los Angeles on July 30, researchers said,

The scene is reconstructed using a depth sensor, allowing the participants to actually occupy the same 3D space as a computer-generated character or object, rather than superimposing one video feed onto another.

According to the researchers, a colour camera and depth sensor were used to create a real-time, HD-video-textured 3D reconstruction of the bench, surroundings, and participants. Mahler explained,

The bench itself plays a critical role. Not only does it contain haptic actuators, but it constrains several issues for us in an elegant way. We know the location and the number of participants, and can infer their gaze. It creates a stage with a foreground and a background, with the seated participants in the middle ground.

It even serves as a controller; the mixed reality experience doesnt begin until someone sits down and different formations of people seated create different types of experiences, he added.

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Disney makes artificial intelligence a group experience - YourStory.com

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We haven't quite reached the terrifying sci-fi hellscape described by the Terminator franchise, but researchers at Facebook have brought us just a bit closer to the age of the machines. Recently, they pulled the plug on an artificial intelligence system after it developed its own language.

The AI in question was actually designed to maximize efficiency in language, but according to Fast Co. Design, the researchers forgot to add a crucial rule in its programming: the language had to be English. So the "two AI agents" moved on with their programming to communicate as efficiently as their programming would allow, putting the conversation between the two outside the understanding of humans.

"Agents will drift off understandable language and invent codewords for themselves," Georgia Tech research scientist Dhruv Batra said. This isn't anything new, either. It's something that keeps cropping up when researchers experiment with this type of AI.

The purpose of these particular Facebook AI agents is to communicate in English, so programmers reworked the code to get the AI back on track. But if AI is allowed to keep to its own devices, Fast Co. Design said, it eventually creates a language all its own. One that can't be understood by human beings.

Now is the perfect time to prepare yourself for the end of humanity's rein over Earth by watching the new 4K Blu-ray of Terminator 2. It seems less a blockbuster action film from the '90s and more of a dark fortelling of our grim future under the emotionless rule of the machines. Regardless of our impending doom, it's a great movie.

Seth Macy is IGN's weekend web producer and just wants to be your friend. Follow him on Twitter @sethmacy, or subscribe to Seth Macy's YouTube channel.

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Artificial Intelligence Develops Its Own Language - IGN

Adobe announced Thursday that Adobe Target is being upgraded with Sensei, the companys framework for artificial intelligence.

Adobe Target is Adobes testing and optimization platform, and will now become the personalization engine of the marketing cloud, says Kevin Lindsay, director of product marketing at Adobe Target.

Adobe is aiming to make the creative development process easier with one-touch personalization across channels including email marketing, mobile, and connected devices.

Brands are really struggling with personalization because different people care about different lines of businesses, says Lindsay. This struggle is just compounded by mobile technology and connected experiences.

A/B testing enables the analysis of multiple variations of content, and is the most common way that email marketers personalize messages, but Adobe Target will now be able to significantly expand its testing capabilities with the help of Sensei by automatically targeting customers for personalized experiences instead.

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Sensei uses machine learning to determine the best experience for the individual. Marketers can then quickly deliver that experience across digital properties with one-click personalization, as Adobe Target uses Sensei to continuously update a customers profile and preferences after every action.

An automated offer feature also helps marketers send the best promotional offer to subscribers who are predicted to be most interested in that content. This could be especially helpful for email marketers during times of high traffic, such as the holidays. Adobe has also added a backup policy, so marketers can hold back a certain amount of traffic and only send new content to a control group.

Sensei takes manual optimization to the next level because it takes all variables in to consideration, says Lindsay. We dont believe that any human can possible appreciate whats happening on a large scale when millions of people are coming to a site. Real-time signals can tell a story that might not immediately be obvious to us mere mortals.

The solution also contains visualization of analytics so marketers can see trends and quickly react to them, and variables that are having an impact on an experience can be pulled to the surface.

Lindsay says creative teams should not feel threatened by the machines.

Putting creative in front of the right people at scale will allow marketers to be even more creative, he says. It can better ensure the right people are seeing the right products and efforts.

In addition, Adobe announced plans to a launch the beta version of a new recommendations algorithm in September. Lindsay says the recommendation engine has been outperforming previous algorithms by as much as 60%, and will be available for email marketers.

Its inspired by natural language, explains Lindsay. It basically does an analysis of a customers entire online behavior, and starts to look at the signal these interactions provide. As the machine ingests more and more data, it begins to interpret them almost like words.

Finally, Adobe hinted at a new open technology the company is working on that will allow brands to plug in their own proprietary algorithms into Adobe Target for customized personalization. The tool is not yet available, but Adobe says they it will provide more details once product development is completed next year.

The standard pricing for Adobe Target includes more rules-based targeting, such as A/B testing, but the premium version has now been upgraded with Sensei. Subscribers to the Adobe Marketing Premium product will be able to access the new personalization solution Friday morning when they enter their office.

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Adobe Target Upgraded With Artificial Intelligence - MediaPost Communications

LONDON

A new technique using artificial intelligence to predict where deforestation is most likely to occur could help the Democratic Republic of Congo (DRC) preserve its shrinking rainforest and cut carbon emissions, researchers have said.

Congo's rainforest, the world's second-largest after the Amazon, is under pressure from farms, mines, logging and infrastructure development, scientists say.

Protecting forests is widely seen as one of the cheapest and most effective ways to reduce the emissions driving global warming.

But conservation efforts in DRC have suffered from a lack of precise data on which areas of the country's vast territory are most at risk of losing their pristine vegetation, said Thomas Maschler, a researcher at the World Resources Institute (WRI).

"We don't have fine-grain information on what is actually happening on the ground," he told the Thomson Reuters Foundation.

To address the problem Maschler and other scientists at the Washington-based WRI used a computer algorithm based on machine learning, a type of artificial intelligence.

The computer was fed inputs, including satellite derived data, detailing how the landscape in a number of regions, accounting for almost a fifth of the country, had changed between 2000 and 2014.

The program was asked to use the information to analyze links between deforestation and the factors driving it, such as proximity to roads or settlements, and to produce a detailed map forecasting future losses.

Overall the application predicted that woods covering an area roughly the size of Luxembourg would be cut down by 2025 releasing 205 million metric tons of carbon dioxide (CO2) into the atmosphere.

The study improved on earlier predictions that could only forecast average deforestation levels in DRC over large swathes of land, said Maschler.

"Now, we can say: 'actually the corridor along the road between these two villages is at risk'," Maschler said by phone late on Thursday.

The analysis will allow conservation groups to better decide where to focus their efforts and help the government shape its land use and climate change policy, said scientist Elizabeth Goldman who co-authored the research.

The DRC has pledged to restore 3 million hectares (11,583 square miles) of forest to reduce carbon emissions under the 2015 Paris Agreement, she said.

But Goldman said the benefits of doing that would be outweighed by more than six times by simply cutting predicted forest losses by 10 percent.

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Researchers: Artificial Intelligence Can Help Fight Deforestation in Congo - Voice of America

By Anthony Aguirre, Ariel Conn and Max Tegmark

Should artificial intelligence be regulated? Can it be regulated? And if so, what should those regulations look like?

These are difficult questions to answer for any technology still in development stages regulations, like those on the food, pharmaceutical, automobile and airline industries, are typically applied after something bad has happened, not in anticipation of a technology becoming dangerous. But AI has been evolving so quickly, and the impact of AI technology has the potential to be so great that many prefer not to wait and learn from mistakes, but to plan ahead and regulate proactively.

In the near term, issues concerning job losses, autonomous vehicles, AI- and algorithmic-decision making, and bots driving social media require attention by policymakers, just as many new technologies do. In the longer term, though, possible AI impacts span the full spectrum of benefits and risks to humanity from the possible development of a more utopic society to the potential extinction of human civilization. As such, it represents an especially challenging situation for would-be regulators.

Already, many in the AI field are working to ensure that AI is developed beneficially, without unnecessary constraints on AI researchers and developers. In January of this year, some of the top minds in AI met at a conference in Asilomar, Calif. A product of this meeting was the set of Asilomar AI Principles. These 23 principles represent a partial guide, its drafters hope, to help ensure that AI is developed beneficially for all. To date, over 1,200 AI researchers and over 2,300 others have signed on to these principles.

Yet aspirational principles alone are not enough, if they are not put into practice, and a question remains: is government regulation and oversight necessary to guarantee that AI scientists and companies follow these principles and others like them?

Among the signatories of the Asilomar Principles is Elon Musk, who recently drew attention for his comments at a meeting of the National Governors Association, where he called for a regulatory body to oversee AI development. In response, news organizations focused on his concerns that AI represents an existential threat. And his suggestion raised concerns with some AI researchers who worry that regulations would, at best, be unhelpful and misguided, and at worst, stifle innovation and give an advantage to companies overseas.

But an important and overlooked comment by Musk related specifically to what this regulatory body should actually do. He said:

The right order of business would be to set up a regulatory agency initial goal: gain insight into the status of AI activity, make sure the situation is understood, and once it is, put regulations in place to ensure public safety. Thats it. Im talking about making sure theres awareness at the government level.

There is disagreement among AI researchers about what the risk of AI may be, when that risk could arise, and whether AI could pose an existential risk, but few researchers would suggest that AI poses no risk. Even today, were seeing signs of narrow AI exacerbating problems of discrimination and job loss, and if we dont take proper precautions, we can expect problems to worsen, affecting more people as AI grows smarter and more complex.

The number of AI researchers who signed the Asilomar Principles as well as the open letters regarding developing beneficial AI and opposing lethal autonomous weapons shows that there is strong consensus among researchers that we need to do more to understand and address the known and potential risks of AI.

Some of the principles that AI researchers signed directly relate to Musks statements, including:

3) Science Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

4) Research Culture: A culture of cooperation, trust and transparency should be fostered among researchers and developers of AI.

5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

20) Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.

21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

The right policy and governance solutions could help align AI development with these principles, as well as encourage interdisciplinary dialogue on how that may be achieved.

The recently founded Partnership on AI, which includes the leading AI industry players, similarly endorses the idea of principled AI development their founding document states that where AI tools are used to supplement or replace human decision-making, we must be sure that they are safe, trustworthy and aligned with the ethics and preferences of people who are influenced by their actions.

And as Musk suggests, the very first step needs to be increasing awareness about AIs implications among government officials. Automated vehicles, for example, are expected to eliminate millions of jobs, which will affect nearly every governor who attended the talk (assuming theyre still in office), yet the topic rarely comes up in political discussion.

AI researchers are excited and rightly so about the incredible potential of AI to improve our health and well-being: its why most of them joined the field in the first place. But there are legitimate concerns about the possible misuse and/or poor design of AI, especially as we move toward advanced and more general AI.

Because these problems threaten society as a whole, they cant be left to a small group of researchers to address. At the very least, government officials need to learn about and understand how AI could impact their constituents, as well as how more AI safety research could help us solve these problems before they arise.

Instead of focusing on whether regulations would be good or bad, we should lay the foundations for constructive regulation in the future by helping our policy-makers understand the realities and implications of AI progress. Lets ask ourselves: how can we ensure that AI remains beneficial for all, and who needs to be involved in that effort?

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Should Artificial Intelligence Be Regulated? - HuffPost