What is Pizzagate? The fake news scandal involving Wikileaks and Hilary Clinton explained – and why its trending amid Epstein inquiry – The Scotsman

NewsPoliticsA Sky documentary that investigates some of the most mind-boggling conspiracy theories of recent years has shone a new light on some of the most baffling fake news stories to come out of the US

Tuesday, 16th June 2020, 8:27 am

After Truth: Disinformation and the Cost of Fake News aired in early June, and surveys the effects of disinformation campaigns on social media and the impacts of well known conspiracy theories.

One of those theories is that of Pizzagate, and the film follows the growth of the story on forums like Reddit and 4chan, how it was fomented by the alt-right and Alex Jones, and then translated into a real-life dangerous situation.

Heres everything you need to know:

Pizzagate was a widely discredited news story which linked Hilary Clintons presidential campaign with a fictional human trafficking ring.

Its so-called because the alleged headquarters of the operation was the Comet Ping Pong pizzeria in Washington, D.C, which according to the conspiracy was also a meeting ground for Satanic ritual abuse.

It all began in March 2016, when the personal email account of John Podesta, Clinton's campaign manager, was hacked.

WikiLeaks published the emails later that year; conspiracy theorists claimed the emails contained coded messages that alluded to human trafficking and a child sex ring.

The emails contained multiple references to pizza and pizza restaurants, but there is no evidence that they are code or refer to anything else.

Had the claims been true, it would have implicated a number of high-ranking Democratic Party officials.

How was the story debunked?

The story has been widely debunked by a number of fact checking a news organisations from across the political spectrum even Fox News has said the story is completely false.

Theorists claimed that similarities between Comet Ping Pongs logo contained symbols linked to Satanism and paedophilia; the New York Times noted these similarities could be found in the logos of completely unrelated companies, if you looked hard enough.

Claims of a secret underground network beneath Comet Ping Pong were disproven by the fact the establishment has no basement, and evidence that John Podesta played a part in the kidnapping of Madeleine McCann were simply sketches of a suspect taken from the descriptions of two eyewitnesses.

No alleged victims have come forward and no physical evidence has been found.

Despite the theory having zero evidence to support it, that didnt stop those who opposed Hilary Clinton believing the story wholesale.

That included gunman Edgar Maddison Welch, who travelled down from South Carolina to confront the owners of Comet Ping Pong.

He entered the pizza restaurant in Washington D.C. packed with families on a Sunday afternoon and fired an automatic rifle.

Thankfully, no one was injured in the disturbance; Mr Welch told police he had driven from South Carolina to investigate the restaurant after reading online reports.

Why is Comet Ping Pong back in the news?

Though its been four years since the height of the Pizzagate story, the owners still have to deal with death threats and abuse.

As employees continue to search for a new rhythm [during the coronavirus pandemic], say the Washington Post, they still field calls from Pizzagate obsessors.

A few weeks ago, someone jammed the phone line for an entire day, frustrating customers who struggled to place orders. [Comet] has received almost 70 Pizzagate messages in recent weeks.

There also seems to be a renewed interest in the false story in the wake of news that US prosecutors want a face-to-face interview with Prince Andrew over the Jeffrey Epstein scandal.

The story has been trending on Twitter again, despite remaining completely untrue, with theorists linking Epsteins private jet the Lolita Express and his private Epstein Island with the restaurant.

There is no evidence to suggest any of it is true.

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What is Pizzagate? The fake news scandal involving Wikileaks and Hilary Clinton explained - and why its trending amid Epstein inquiry - The Scotsman

Wikileaks Leaks Show That Retired Police Commissioner Hussein ALi And Former First Lady Lucy Kibaki Ordered For The Killing Of Prominent Politicians -…

Leaked letters by Wikileaks now show that former first lady Lucy kibaki and retired police commissioner Major General Hussein Ali had ordered the killing of prominent politicians, including Martha Karua and Gitobu Imanyara.

According to the written by a policeman (Wilfred Njenga) who claims to be a member of the defunct Kwekwe Squad, among the prominent people who were monitored for possible assassination were Paul Muite, Ferdinand Waititu, GG Kariuki, Bonny Khalwale, Gitobu Imanyara, Martha Karua and businesswoman Mary Wambui.

According to the author, by the time the 200/08 post-election violence calmed down, the killer squad alone had killed at least 1,869 Mungiki members and 631 suspected robbers. He alone had killed 40 people, and for that they were paid an allowance of Ksh25,000 allowance on a wekly basis.

Read: Kirinyaga Legislators Divided Over Waiguru Ouster Ahead Of Senate Hearing

He claims that President Mwai Kibaki was not aware of the killings, and they were masterminded by powerful people in the government. They would rehearse the assasinations by killing prominent businessmen, though some of the target were not killed.

Tafadhali madam utauwawa just go away into exile because we know it will not take long for Maj Gen Ali to issue kull order. Mr Muthaura, Mr Michuki, Maj Gen Ali and Lucy Kibaki are the ones issues orders to track prominent personalities, read the letter addressed to Martha Karua in part.

The unit to carry out the assassinations was to be paid Ksh 150, 000 each, the letter says.

At least a dozen police officers who conducted the killings died or disappeared, according to the letter, and the latest to die was former head of Special crimes prevention unit Richard Katola who died in 2015.

Read: MP Rigathi Gachagua Wants DPP To Probe Video In Which He Is Accused Of Organising Chaotic Protests

The then interior Minister late George Saitoti was kept in the dark but was used to issue statements, and died in a suspicious plane crash in 2012. It is suspected that he was assassinated.

Prof George Saitoti and his PS Kimemia are kept in darkness but used to issue statements and reports at Parliament and in Public Barazas in support of police without knowing they are being used, adds the letter.

In order to guard any information from reaching the targets, the letter reveals that National Intelligence Service (NIS) officers were deployed at Post Offices to screen all letters addressed to MPs and prominent people.

We are told First Lady Lucy Kibaki called Mr Muthaura (Francis) and Maj Gen Ali and ask them to eliminate Muite, the letter adds.

Here is the leaked letter:-

Email your news TIPS tonews@kahawatungu.comor WhatsApp +254708677607. You can also find us on Telegram throughwww.t.me/kahawatungu

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Wikileaks Leaks Show That Retired Police Commissioner Hussein ALi And Former First Lady Lucy Kibaki Ordered For The Killing Of Prominent Politicians -...

10 Essential TED Talks on Artificial Intelligence

In the past few years, theres been a lot of discussion around Artificial Intelligence and its implications for everything from industrial applications to smart phone appsand if you have a smart phone, chances are youve come across TED Talks.

If you havent listened to a TED Talk, you should. Presented by people who are deeply connected to the field they are speaking about, it gives you the opportunity to listen to people with an insiders expertise that most of us would never hear from, but who can provide valuable perspectives.

So whether or not youve ever seen a TED Talk, if youve been looking to know more about the current state and future direction of Artificial Intelligence in our world, these 10 TED Talks are essential presentations to help you become fully informed about the state of this revolutionary technology.

Presented by Educator and Entrepreneur Sebastian Thrun & TED Conference Curator Chris Anderson, this Ted Talk is an excellent overview of what people talk about when they talk about artificial intelligence, what people are concerned about, and why.

Some of the highlights include why artificial intelligence is having its breakout moment now, how neural networksthe powerful algorithms that allow software to learn new things, an essential development on the road to a generally intelligent AI, and why we should not fear a runaway AI in the future.

Presented by Bruno Michel, a Computer Research Engineer and member of the US National Academy of Engineering, this TED Talk addresses the elephant in the room for many people in the room when it comes to artificial intelligence: wont it turn against us?

Michel explains the basis for fears expressed by people like Elon Musk that AIs will come to dominate humans in the future before giving his view that engaging in mental fitness exercises, much like we jog for physical exercise, we can build up our collective brain power to remain competitive with an advanced AI.

Presented by Margaret Mitchell, an AI research scientist at Google, relates to us her experience working with computer intelligence and give a warning about the unconscious biases we build into our technology.

Her advice to all of us is in order to develop a beneficial artificial intelligence, we have to start coming together as a society and begin to decide on the path and direction we wish artificial intelligence to take in the future.

Presented by Robin Hauser, documentary filmmaker of the award-winning film CODE:Debugging the Gender Gap and is currently producing a film on the subject of unconscious biases and its impact on society.

Like Mitchell, Hauser details her experience working with unconscious biases and how standards need to be developed to govern the development of artificial intelligence sooner rather than later in order to keep implicit biases out of deep learning algorithms.

Presented by Zeynep Tufekci, a Techno-sociologist working on how our societies intersect with digital connectivity, this TED Talk is a reminder that human morality and our embrace of it is a key safeguard against a possible runaway artificial intelligence.

By exploring how we are already using AIs to make decisions once the sole responsibility of humans, Tufekci explains how we cannot abdicate our moral responsibilities for the unpredictable behavior of the machines we create.

Presented by Stuart Russell, a leading figure in the world of AI development, this Talk discusses the threat of the value alignment problem, where what we say we want is actually different from what we actually desire as it relates to artificial intelligence.

His solution to this problem is a prescription of 3 general rules that should govern the future development of AI to ensure that it is a benefit to humanity and not a detriment or threat.

Presented by Max Tegmark, a physicist and AI researcher at MIT, this Talk discusses what the real challenges presented by artificial intelligence are, as opposed to uninformed speculation.

By laying out procedures for artificial intelligence research and development, Tegmark says, we can guide AI development away from the potential hazards and direct it towards the world-altering benefits that a beneficial AI system represents.

Presented by Kai-Fu Lee, one of the leading entrepreneurs and venture capitalists in the Chinese Technology industry, Lee recounts his own experience of almost robotic, machine-like dedication to work and how it nearly destroyed his life.

By eliminating jobs that stifle and detract from peoples humanity through crushing, routine work, Lee says, artificial intelligence presents human beings with the opportunity to create entirely new industries built around compassion, community, and kindness where people can work in ways that reinforce their humanity rather than smother it.

Presented by Grady Booch, a scientist, and philosopher with IBM, this Talk delves into all of the fears people have about an artificial superintelligence and their origins in cultural panic, not actual science.

Booch explains how artificial intelligence will develop the morality we want it to possess as we teach it the kinds of human values that will ensure it will be a benefit to humanity, which is too significant to pass up because of unfounded fears of a malevolent AI.

Presented by Garry Kasparov, the chess player, widely considered the best in the world, who famously lost a chess match in 1997 to IBMs Deep Blue.

Now an advocate for global democracy and human rights, Kasparov could be forgiven if he distrusted artificial intelligence and the governments who might wield them.

Instead, Kasparov shares his hopes and visions for a world in which artificial intelligence can advance the cause of humanity beyond what many believe possible.

Rather than surrender to our fears, Kasparov says, we must conquer them for the final good of humanity, who stand only to benefit from artificially intelligent systems who share our values, values we can instill and inspire in these systems.

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10 Essential TED Talks on Artificial Intelligence

Best Colleges with Artificial Intelligence Degrees

1 University of Pennsylvania Philadelphia, PA

University of Pennsylvania offers 2 Artificial Intelligence Degree programs. It's a large private university in a large city. In 2015, 44 students graduated in the study area of Artificial Intelligence with students earning 44 Master's degrees.

Carnegie Mellon University offers 2 Artificial Intelligence Degree programs. It's a large private university in a large city. In 2015, 64 students graduated in the study area of Artificial Intelligence with students earning 45 Master's degrees, and 19 Doctoral degrees.

University of Southern California offers 1 Artificial Intelligence Degree program. It's a large private university in a large city. In 2015, 12 students graduated in the study area of Artificial Intelligence with students earning 12 Master's degrees.

University of Pittsburgh-Pittsburgh Campus offers 2 Artificial Intelligence Degree programs. It's a large public university in a large city. In 2015, 4 students graduated in the study area of Artificial Intelligence with students earning 2 Master's degrees, and 2 Doctoral degrees.

Georgia Institute of Technology-Main Campus offers 1 Artificial Intelligence Degree program. It's a large public university in a large city. In 2015, 7 students graduated in the study area of Artificial Intelligence with students earning 7 Doctoral degrees.

University of Washington-Seattle Campus offers 2 Artificial Intelligence Degree programs. It's a large public university in a large city. In 2015, 27 students graduated in the study area of Artificial Intelligence with students earning 27 Master's degrees.

Syracuse University offers 1 Artificial Intelligence Degree program. It's a large private university in a mid sized city. In 2015, 1 students graduated in the study area of Artificial Intelligence with students earning 1 Master's degree.

University of Georgia offers 1 Artificial Intelligence Degree program. It's a large public university in a mid sized city. In 2015, 9 students graduated in the study area of Artificial Intelligence with students earning 9 Master's degrees.

South Dakota School of Mines and Technology offers 0 Artificial Intelligence Degree programs. It's a small public university in a small city.

Eastern Michigan University offers 1 Artificial Intelligence Degree program. It's a large public university in a large suburb. In 2015, 1 students graduated in the study area of Artificial Intelligence with students earning 1 Certificates degree.

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Best Colleges with Artificial Intelligence Degrees

Artificial Intelligence | Tools, Publications & Resources

Artificial intelligence seeks to create intelligent machines that work and react more like humans. AI developments rely on deep learning, machine learnings, and natural language processing that help computers accomplish specific tasks by processing large amounts of training data to help the system recognize patterns, input data to drive predictions, and feedback data for improving accuracy over time.

One of the big stories highlighting AIs development and reach was the AlphaGo programs victory over 18-time Go world champion Lee Sedol in a five-game series in 2016. In an article in Nature, DeepMind researchers explained the development of AlphaGo's expertise through a combination of Monte-Carlo tree search (an algorithm for optimal decision making) and deep neural networks that have been trained via supervised learning, observing human expert games, and reinforced by playing games against itself. [1] A year later, in 2017, AlphaGo had another successful outing, defeating a team of five Go champions and then demonstrating a collaborative match where two teams, each composed of a human and an AlphaGo companion, played against each other the researchers celebrated the collaborative approach as a future direction for AI where humans would work in step with Artificial Intelligence to elevate overall performance. [2]

If Googles DeepMind AlphaGo represented the positive developments toward AI, Microsofts Tay artificial intelligence chat bot represented the challenges and limits of the technology. Microsofts research team launched the AI chatbot on Twitter, GroupMe, and Kik as a way to test and improve Microsoft's understanding of conversational language, including the nuances of teens online language. [3] The bot quickly began issuing offensive posts (disputing the existence of the Holocaust, referring to women and minorities with unpublishable words, and advocating genocide), partly in response to user commands for the bot to repeat users own statements, while also learning bad behavior as it ingested content from its social media forums. [4] Microsoft apologized for the unintended offensive tweets and tried to explain some of what happened while recognizing the pilot as part of a process for moving forward with the technology. [5] The experience with Tay could actually limit artificial intelligence development, as some technology companies have become reluctant to set conversational artificial intelligence systems free to talk with the large numbers of people needed to train them. [6]

Technology companies are finding roles for artificial intelligence in moderating online content. Facebooks artificially intelligent language processing engine, Deep Text, applies deep learning to understand human language the company initially pursued Deep Text to power chatbots in Messenger, to filter out spam and abusive comments from users Newsfeeds, and to help understand the topic area and even the content of just about anything people post on the social network. [7] The system quickly surpassed humans in flagging offensive photos, quarantining obscene content before it ever reaches users. [8] As Facebooks use of AI has advanced, it has begun to explore artificial intelligences use in flagging material on the video platform Facebook Live, which requires computer vision algorithms that are fast, know how to prioritize policies, and when content should be taken down. [9] Facebook also sees opportunities for artificial intelligence to teach itself to identify key phrases that were previously flagged for being used to bolster a known terrorist group, to identify users who create fake accounts in order to spread extremist or terrorist content, or to identify users associated with clusters of pages or groups that promote extremist content. [10] In 2017, Facebook announced plans to integrate AI into a program that allowed users to flag troubling image or status posts, helping to identify posts that suggest that a user may be suicidal; Facebook partnered with organizations like the National Suicide Prevention Lifeline, the National Eating Disorder Association, and the Crisis Text Line so that when users posts are flagged, they can connect immediately via Messenger. [11] Facebooks suicide prevention program evolved to the point that the technology can proactively identify a post or Facebook Live broadcast "likely to include thoughts of suicide," and send those posts to Facebook's trained reviewers who, in turn, can contact first responders. [12]

Facebook has continued to pursue AI as a tool to better understand content on the network, including its Automatic Alternative Text tool which uses deep neural networks to identify particular objects in a photo and pick out particular characteristics of the people in the photo to create a caption that a text-to speech engine can then read aloud for users with low visibility while the system doesnt always get images exactly correct, it is an improvement and shows the growing potential for AI to recognize and describe photos and images. [13] Facebook is also exploring how artificial intelligence can process content and make suggestions based on that content. By integrating AI into its personal assistant technology M, Facebook can suggest users book an Uber or prompt them to send money to a friend based on whatever it is the user was talking about in Messenger. [14] And Facebook developers have also used deep learning and neural networks to train its Lumos system to recognize scenes, objects, animals, places, attractions, and clothing items in photos, allowing users to search for and retrieve photos even if they themselves have not annotated them. [15]

In addition to content moderation, artificial intelligence is increasingly being used for content generation. From short films (Sunspring by the AI program Benjamin), to podcasts (Sheldon County), to short stories (Shelley), artificial intelligence systems are being used to develop creative or artistic outputs. [16] AI is also increasingly used to evaluate artistic outputs, such as a system of neural networks developed by Disney and the University of Massachusetts Boston that can evaluate short stories to predict which stories will be most popular by looking at different sections of each story and the holistic view of a story's meaning. [17]

AI is also being used to develop informational content and news reporting. Systems like IBMs Watson are providing real-time scores, assessments, and automated video captions for a range of sporting events and cultural activities. [18] Newspapers are turning to AI to produce news coverage, such as The Washington Posts use of its Heliograf artificial intelligence program to cover every House, Senate, and gubernatorial race on election day, freeing up reporters to focus on high-profile contests. [19]

And artificial intelligence is also being integrated into education. The IBM Foundation and the American Federation of Teachers have collaborated to build Teacher Advisor, a program that uses artificial intelligence technology to answer questions from educators and help them build personalized lesson plans. [20]

These advances are all in addition to the ways that artificial intelligence research will transform higher education and research centers. IBM and MIT have signed a 10-year, $240 million partnership agreement that establishes the MIT-IBM Watson AI Lab where IBM researchers and MIT students and faculty will work side by side to conduct advanced AI research. [21]

As artificial intelligence makes its way into more and more sectors, the dominant concern remains the potential impact it will have on the workforce. A 2018 Gallup survey found that the American public widely embraces artificial intelligence in attitude and practice, with nearly five in six Americans already using some product or service featuring AI, but most Americans recognize the technologies potential impact on future employment. [22] Those concerns for employment are supported by ample research. A 2018 report from PwC predicts three waves of automation a flood of algorithms where machines handle data analysis and simple digital tasks; augmentation inundation, when repeatable tasks and the exchange of information will come to be done by humans and automated systems working together; and, finally, an autonomy tsunami, when machines and software will make decisions and take physical actions with little or no human input with experts noting that most developed countries are already well into the first stage. [23] Still other research places AIs development and threat in a more nuanced context. An AI Indexcreated by researchers at Stanford University and the Massachusetts Institute of Technology, a McKinsey Global Institute report, and a National Bureau of Economic Research article by economists from M.I.T. and the University of Chicago collectively suggest that AI can likely do less now than we think, but that it will eventually do more in more sectors than we could expect, and that it will probably evolve faster than past technologies. [24] As important as the question of when, might be the question of where geographically and in which sectors. Several reports (a 2017 study from Northwestern University and MIT and a 2017 report from the Institute for Spatial Economic Analysis at the University of Redlands) indicate that AI might have its greatest effects on cities where more jobs are routine clerical work, such as cashier and food service jobs, which are more susceptible to automation while that could include larger cities like Las Vegas, Orlando, and Louisville, it could also include smaller cities with fewer than 100,000 people, where such jobs may have higher concentrations. [25] As routine service and clerical jobs become susceptible to automation, other industries that rely on skills in statistics, mathematics, and software development, will likely see growth or stability, as they build and improve the systems that replace traditional manufacturing and service workers. [26]

A preview of AIs potential impact on clerical work might be available in Google Duplex. At its 2018 I/O conference Google debuted its Google Duplex AI System, which helps Google Assistant accomplish real-world tasks over the phone (book an appointment, make reservations) initially, the system only operates in closed domains (exchanges that are functional, with strict limits on what is going to be said) and will have disclosure built-in so that a verbal announcement will be made to the person on the other end of the call. [27] Google has begun to explore options for Duplexs use in call centers to improve call handling by giving the common but simple queries to Duplex, leaving a limited number of human workers to field more advanced call issues. [28] In a similar vein, IBM Watson and Japanese insurance company Fukoku Mutual Life Insurance introduced an AI solution that can scan hospital records and other documents to determine insurance payouts, factoring injuries, patient medical histories, and procedures administered the system will replace 34 human insurance claim workers. [29]Googles Duplex is just one of several initiatives to make artificial intelligence systems that can communicate more like humans and accomplish more human tasks. IBMs Project Debater seeks tointeract and debate with people across 100 topics the current scope of interactions are tightly constrained to a four-minute opening statement, followed by a rebuttal to the opponents argument, and then a statement summing up a viewpoint. [30] Amazons Alexa Prize competition has researchers create a chatbot using Alexa that can talk to a human for 20 minutes without messing up. [31]

Even if AI does not fully replace jobs, there is a clear desire to use AI to augment work. Googles DeepMind has begun exploring avenues into healthcare with the creation of DeepMind Health that will create apps to help medical professionals identify patients at risk of complications and organize and prioritize admitted patients while neither of the initial products use artificial intelligence, deep learning, or neural networks, the entry into the space indicates their longer-term interest in the technologys deployment in this space. [32]

Through all of these developments, governments will increasingly consider the technologys potential effects on the economy and innovation. The U.S. government has accelerated its focus on artificial intelligence, hosting a White House summit on artificial intelligence that included representatives from 38 companies (including Amazon, Facebook, Google, and Intel) to discuss how the government can fund AI research and alter regulations to advance the technology and announcing a Select Committee on Artificial Intelligence made of up the leading AI researchers in government and charged with advising the White House on governmentwide AI research and development priorities and the establishment of partnerships between government, the private sector, and independent researchers. [33] The Trump administration has pledged to release more government data that might help fuel AI research in the U.S., but what kind of data would be released or who would be eligible to receive the information remains unclear. [34]

Artificial intelligence could become an invaluable tool for organizing and making accessible large collections of information. Googles Life Tags project is a searchable archive of Life magazine photographs that used artificial intelligence to attach hundreds of tags to organize the archive. [35] Another Google project, Talk to Books, lets users type in a statement or a question and the system retrieves whole sentences in books related to what was typed, with results based not on keyword matching, but on more complex training of AI to identify what a good response looks like. [36] The Allen Institute for Artificial Intelligence, a nonprofit created by Microsoft co-founder Paul Allen, unveiled Semantic Scholar, a search engine that uses machine learning and other AI to improve the way academics search through the growing body of public research, more easily accessing research papers, targeting specific results, and revealing images, by using natural language processing algorithms and computer vision technology. [37]

As AI becomes more adept at generating content, it could further complicate users navigation of a complex information environment. Artificial intelligence will be able to create 3D face models from a single 2D image; manipulate facial expressions on video in real time using a human puppet; change the light source and shadows in any picture; generate sound effects based on mute video; and resurrect characters using old clips and many of these effects have given rise to the deep fakes that manipulate video and other images. [38]As with many other technologies, AI may become one more development that libraries help communities better understand. Facebook launched a campaign to educate people on the basics of artificial intelligence, focusing on the technology behind photo recognition, self-driving cars, and language translation. [39] In a similar way, the Urban Libraries Council (ULC) articulated a vision for libraries to serve communities by advancing algorithmic literacywhile also ensuring an equitable and inclusive future by monitoring the storage, privacy, and application of data as AI technology becomes more ubiquitous.

If AI becomes a serious threat to jobs, libraries roles in workforce development may become even more important, but also more complicated. A compounded challenge may arise where workforce development will need to encompass not only the preparation for entry level individuals (into a market that is increasingly limited and competitive), but also solutions for a new vacuum in middle level management caused by the elimination of once plentiful entry level workers who matriculated into middle management. [40] The new workforce development demands will likely require higher-order critical, creative, and innovative thinking as well as emotional engagement, placing a greater value on the quality of thinking, listening, relating, collaborating, and learning. [41]

AIs dependence on data sets can reinforce certain human systems, including bias. [42] Many researchers and practitioners are exploring options to address sexism and racism in AI development by curating new data sets that balance gender and ethnicity and more intentionally labeling and annotating data sets to show how the sets were collected. [43] To help change the way AI understands LGBT-related content, GLADD announced a partnership with Alphabets Jigsaw division to train AI with positive LGBT-related content and distinguish between phrases that are offensive to the LGBT community and those that are acceptable. [44] Coupled with efforts to change the scope and nature of data that trains AI systems are efforts to recruit women and other underrepresented groups into the field of artificial intelligence. [45]

Issues of sexism, racism, and bias are just part of the larger ethical concerns around AI. In 2017, Google launched a DeepMind ethics group to oversee the responsible development of artificial intelligence by helping developers put ethics into practice and educating society about the potential impacts of AI. [46] A 2018 report, authored by two dozen researchers from Oxford, Cambridge, OpenAI, the Electronic Frontier Foundation, Endgame, and the Center for a New American Security, focused on the potential negative effects of AI, including malicious uses of the technology. [47] While computer science programs have been required to provide students with an understanding of ethical issues related to computing in order to be accredited by ABET, a growing number of universities are launching new courses on the ethics of artificial intelligence, the ethical foundations of computer science, and other offerings that will help train the next generation of technologists and policymakers to consider the ramifications of innovations before those products are made available to the public. [48] As technologist are increasingly motivated to consider the ethical implications of their innovations, religion, philosophy, and the humanities could play an increasingly important role in the development of artificial intelligence. [49]

Many technology leaders are working to open the artificial intelligence field to make it more collaborative. Organizations like OpenAI, which was established by tech leaders like Elon Musk, Peter Thiel, and Reid Hoffman, promote a beneficial goal of advancing digital intelligence in ways that benefit humanity, free from the demand to generate financial return. [50] Facebook, Amazon, Microsoft, Google's DeepMind, and IBM are among the major partners in the Partnership on Artificial Intelligence to Benefit People and Society, which seeks to conduct open-source research and investigate globally important AI issues such as ethics and human and AI system collaboration. [51] In 2016, Apple announced plans to allow its artificial intelligence teams to publish research papers, reversing an earlier strategy to keep their research in-house, in the hopes that engaging with the larger community might allow researchers to feed off wider advances in the field. [52]

Even as artificial intelligence research has sought to become more collaborative, it has also put a strain on traditional systems of research and knowledge production and sharing. Many universities in the United States and Europe are losing talented computer scientists and artificial intelligence experts, lured away from academia by private sector offers the shift from academic settings to the private sector has implications for not only research production and dissemination, but also the teaching and training of future generations. [53] In the United States, some technology companies have shifted their artificial intelligence operations to be closer to the universities that produce leading researchers. Facebook opened new artificial intelligence labs in Seattle and Pittsburgh after hiring three AI and robotics professors from the University of Washington and Carnegie Mellon University in addition to advancing Facebooks research, the professors will be better positioned to recruit and train other AI experts from those universities programs. [54] Still other technology companies have developed research labs with specific commitments to academic institutions Microsofts Research AI unit engaged in a formal partnership with MITs Center for Brains, Minds and Machines. [55]

[1] "Googles AI Is Now Reigning Go Champion of the World," Daniel Oberhaus, Motherboard, March 12, 2016, available from https://motherboard.vice.com/en_us/article/3dak7w/googles-ai-is-now-reig...

[2] "Googles AlphaGo AI defeats team of five leading Go players," Darrell Etherington, TechCrunch, May 26, 2017, available from https://techcrunch.com/2017/05/26/googles-alphago-ai-defeats-team-of-fiv...

[3] Microsoft made a chatbot that tweets like a teen, Jacob Kastreakes, The verge, March 23, 2016, available from https://www.theverge.com/2016/3/23/11290200/tay-ai-chatbot-released-micr...

[4] Microsoft Created a Twitter Bot to Learn from Users. It Quickly Became a Racist Jerk, Daniel Victor, The New York Times, March 24, 2016, available from https://www.nytimes.com/2016/03/25/technology/microsoft-created-a-twitte...

[5] Microsoft shows what it learned from its Tay AI's racist tirade, Jon Fingas, Engadget, March 25, 2016, available from https://www.engadget.com/2016/03/25/microsoft-explains-tay-ai-incident/

[6] To Give A.I. the Gift of Gab, Silicon Valley Needs to Offend You, Cade Metz and Keith Collins, The New York Times, February 21, 2018, available from https://www.nytimes.com/interactive/2018/02/21/technology/conversational...

[7] "Facebook Is Teaching Its Computers to Understand Everything You Post," Will Oremus, Slate, June 1, 2016, available from http://www.slate.com/blogs/future_tense/2016/06/01/facebook_s_new_ai_eng...

[8] "Facebook spares humans by fighting offensive photos with AI," Josh Constine, TechCrunch, May 31, 2016, available from https://techcrunch.com/2016/05/31/terminating-abuse/

[9] "Facebook developing artificial intelligence to flag offensive live videos." Kristina Cooke, Reuters, December 1, 2016, available from https://uk.reuters.com/article/us-facebook-ai-video-idUKKBN13Q52M

[10] "Facebook Will Use Artificial Intelligence to Find Extremist Posts," Sheera Frenkel, The New York Times, June 15, 2017, available from https://www.nytimes.com/2017/06/15/technology/facebook-artificial-intell...

[11] "Facebook leverages artificial intelligence for suicide prevention," Natt Garun, The Verge, March 1, 2017, available from https://www.theverge.com/2017/3/1/14779120/facebook-suicide-prevention-t...

[12] "Facebook's suicide prevention AI can now do more to help people in trouble," Karissa Bell, Mashable, November 27, 2017, available from https://mashable.com/2017/11/27/facebook-ai-suicide-prevention/#4hI.WyNN...

[13] "Facebooks AI is now automatically writing photo captions," Cade Metz, Wired, April 5, 2016, available from https://www.wired.com/2016/04/facebook-using-ai-write-photo-captions-bli...

[14] "Facebook is using AI in private messages to suggest an Uber or remind you to pay a friend," Kurt Wagner, Recode, April 6, 2017, available from https://www.recode.net/2017/4/6/15203526/facebook-messenger-m-artificial...

[15] "Facebook's AI image search can 'see' what's in photos," Billy Steele, Engadget, February 2, 2017, available from https://www.engadget.com/2017/02/02/facebook-ai-image-search/

[16] Please see any of the below as examples:

Movie written by algorithm turns out to be hilarious and intense, Annalee Newitz, ArsTechnica, June 9, 2016, available from https://arstechnica.com/gaming/2016/06/an-ai-wrote-this-movie-and-its-st...

What an infinite AI-generated podcast can tell us about the future of entertainment, James Vincent, The Verge, March 11, 2018, available from https://www.theverge.com/2018/3/11/17099578/ai-generated-podcast-procedu...

AI can write surprisingly scary and creative horror stories, Swapna Krishna, Engadget, October 31, 2017, available from https://www.engadget.com/2017/10/31/shelley-ai-writes-horror-stories-on-...

[17] Disney Research taught AI how to judge short stories, Rob Lefebvre, Engadget, October 21, 2017, available from https://www.engadget.com/2017/08/21/disney-research-taught-ai-to-judge-s...

[18] Please see any of the below as examples:

At This Years U.S. Open, IBM Wants To Give You All The Insta-Commentary You Need, Steven Melendez, Fast Company, September 2, 2016, available from https://www.fastcompany.com/3063369/at-this-years-us-open-ibm-wants-to-g...

Wimbledon to Use IBMs Watson AI for Highlights, Analytics, Helping Fans, Jeremy Kahn, Bloomberg, June 27, 2017, available from https://www.bloomberg.com/news/articles/2017-06-27/wimbledon-to-use-ibm-...

IBM is sending Watson to the Grammys, Brian Mastroianni, Engadget, January 24, 2018, available from https://www.engadget.com/2018/01/24/ibm-watson-grammys/

[19] Washington Post to Cover Every Major Race on Election Day With Help of Artificial Intelligence, Lukas I. Alpert, The Wall Street Journal, October 19, 2016, available from https://www.wsj.com/articles/washington-post-to-cover-every-major-race-o...

[20] Next Target for IBMs Watson? Third-Grade Math, Elizabeth A. Harris, September 27, 2016, available from https://www.nytimes.com/2016/09/28/nyregion/ibm-watson-common-core.html

and

Artificially intelligent math for school educators, A Fine, District Administration, October 27, 2017, available from http://districtadministration.com/artificially-intelligent-math-for-scho...

[21] IBM and MIT pen 10-year, $240M AI research partnership, Ron Miller, TechCrunch, September 6, 2017, available from https://techcrunch.com/2017/09/06/ibm-and-mit-pen-10-year-240m-ai-resear...

[22] Most Americans See Artificial Intelligence as a Threat to Jobs (Just Not Theirs), Niraj Chokshi, March 6, 2018, available from https://www.nytimes.com/2018/03/06/us/artificial-intelligence-jobs.html

[23] Automation is going to hit workers in three waves, and the first one is already here, Erin Winick, MIT Technology Review, February 7, 2018, available from https://www.technologyreview.com/the-download/610211/automation-is-going...

[24] A.I. Will Transform the Economy. But How Much, and How Soon?, Steve Lohr, The New York Times, November 30, 2017, available from https://www.nytimes.com/2017/11/30/technology/ai-will-transform-the-econ...

[25] Small cities face greater impact from automation, Brian Wang, Next Big Future, October 24, 2017, available from https://www.nextbigfuture.com/2017/10/small-cities-face-greater-impact-f...

and

The Parts of America Most Susceptible to Automation, Alana Semuels, The Atlantic, May 3, 2017, available from https://www.theatlantic.com/business/archive/2017/05/the-parts-of-americ...

[26] What Does Work Look Like in 2026? New Statistics Shine Light on Automations Impacts, Erin Winick, MIT Technology Review, October 25, 2017, available from https://www.technologyreview.com/the-download/609218/what-does-work-look...

[27] Googles AI sounds like a human on the phone should we be worried? James Vincent, The Verge, May 9, 2018, available from https://www.theverge.com/2018/5/9/17334658/google-ai-phone-call-assistan...

and

Google now says controversial AI voice calling system will identify itself to humans, Nick Statt, The Verge, May 10, 2018, available from https://www.theverge.com/2018/5/10/17342414/google-duplex-ai-assistant-v...

[28] Google's Duplex AI could soon be running call centers, Chris Merman, The Inquirer, July 6, 2018, available from https://www.theinquirer.net/inquirer/news/3035476/google-duplex-could-so...

[29] Japanese white-collar workers are already being replaced by artificial intelligence, Dave Gershgorn, Quartz, January 2, 2017, available from https://qz.com/875491/japanese-white-collar-workers-are-already-being-re...

[30] IBM Unveils System That Debates With Humans, Cade Metz and Steve Lohr, The New York Times, June 18, 2018, available from https://www.nytimes.com/2018/06/18/technology/ibm-debater-artificial-int...

[31] Inside Amazons $3.5 million competition to make Alexa chat like a human, James Vincent, The Verge June 13, 2018, available from https://www.theverge.com/2018/6/13/17453994/amazon-alexa-prize-2018-comp...

[32] "Google AI group that's mastering Go is now taking on healthcare," Jacob Kastrenakes, Feruary 25, 2016, available from https://www.theverge.com/2016/2/25/11112366/deepmind-health-launches-med...

[33] Amazon, Google and Microsoft to attend White House AI summit, John Fingas, Engadget, May 8, 2018, available from https://www.engadget.com/2018/05/08/white-house-ai-summit/

and

White House Announces Select Committee of Federal AI Experts, Aaron Boyd, NextGov, May 10, 2018, available from https://www.nextgov.com/emerging-tech/2018/05/white-house-announces-sele...

[34] The White House promises to release government data to fuel the AI boom, Will Knight, MIT Technology Review, June 5, 2018, available from https://www.technologyreview.com/s/611331/the-white-house-promises-to-re...

[35] Google used AI to sort millions of historical Life photos you can explore online, James Vincent, The Verge, March 7, 2018, available from https://www.theverge.com/2018/3/7/17091392/google-ai-photo-tagging-life-...

[36] Google AI experiment has you talking to books, Mariella Moon, Engadget, April 14, 2018, available from https://www.engadget.com/2018/04/14/google-ai-experiment-talk-to-books/

[37] Allen Institute for AI Eyes the Future of Scientific Search, Cade Metz, Wired, November 11, 2016, available from https://www.wired.com/2016/11/allen-institute-ai-eyes-future-scientific-...

[38] Artificial intelligence is going to make it easier than ever to fake images and video, James Vincent, The Verge, December 20, 2016, available from https://www.theverge.com/2016/12/20/14022958/ai-image-manipulation-creat...

[39] Facebook: Don't freak out about artificial intelligence, Richard Nieva, CNET, December 1, 2016, available from https://www.cnet.com/news/facebook-artificial-intelligence-filter-bubble...

[40] AI will rob companies of the best training tool they have: grunt work, Sarah Kessler, Quartz, May 11, 2017, available from https://qz.com/979812/how-ai-will-change-the-shape-of-organizations/

[41] In the AI Age, Being Smart Will Mean Something Completely Different, Ed Hess, Harvard Business Review, June 19, 2017, available from https://hbr.org/2017/06/in-the-ai-age-being-smart-will-mean-something-co...

[42] Artificial Intelligences White Guy Problem, Kate Crawford, The New York Times, June 25, 2016, available from https://www.nytimes.com/2016/06/26/opinion/sunday/artificial-intelligenc...

and

AI facial analysis demonstrates both racial and gender bias, Swapna Krishna, Engadget, February 12, 2018, available from https://www.engadget.com/2018/02/12/facial-analysis-ai-has-racial-gender...

[43] AI can be sexist and racist its time to make it fair, James Zhou and Laura Schiebinger, Nature, July 18, 2018, available from https://www.nature.com/articles/d41586-018-05707-8

[44] Googles parent company is using AI to make the internet safer for LGBT people, Maria LaMagna, MarketWatch, March 14, 2018, available from https://www.marketwatch.com/story/how-artificial-intelligence-can-make-t...

[45] The Future of AI Depends on High-School Girls, Lauren Smiley, The Atlantic, May 23, 2018, available from https://www.theatlantic.com/technology/archive/2018/05/ai-future-women/5...

[46] Googles DeepMind Launches Ethics Group to Steer AI, George Dvorsky, Gizmodo, October 4, 2017, available from https://gizmodo.com/google-s-deepmind-launches-ethics-group-to-steer-ai-...

[47] Why artificial intelligence researchers should be more paranoid, Tom Simonite, Wired, February 20, 2018, available from https://www.wired.com/story/why-artificial-intelligence-researchers-shou...

[48] Techs Ethical Dark Side: Harvard, Stanford and Others Want to Address It, Natasha Singer, The New York Times, February 12, 2018, available from https://www.nytimes.com/2018/02/12/business/computer-science-ethics-cour...

[49] Artificial intelligence doesnt have to be evil. We just have to teach it to be good. Ryan Holmes, Recode, November 30, 2017, available from https://www.recode.net/2017/11/30/16577816/artificial-intelligence-ai-hu...

[50] Elon Musk Snags Top Google Researcher for New AI Non-profit," Cade Metz, Wired, December 11, 2015, available from https://www.wired.com/2015/12/elon-musk-snags-top-google-researcher-for-...

[51] "Facebook, Amazon, Google, IBM, Microsoft form new AI alliance," Lance Ulanoff, Mashable, September 9, 2016, available from https://mashable.com/2016/09/29/partnership-on-ai/#2WlFh7QQNqqx

[52] Apple to Start Publishing AI Research to Hasten Deep Learning, Alex Webb, Bloomberg, December 6, 2016, available from https://www.bloomberg.com/news/articles/2016-12-06/apple-to-start-publis...

[53] 'We can't compete': Why universities are losing their best AI scientists, Ian Sample, The Guardian, November 1, 2017, available from https://www.theguardian.com/science/2017/nov/01/cant-compete-universitie...

[54] Facebook adds A.I. labs in Seattle and Pittsburgh, pressuring local universities, Cade Metz, The New York Times, May 4, 2018, available from https://www.nytimes.com/2018/05/04/technology/facebook-artificial-intell...

[55] Microsoft creates an AI research lab to challenge Google and DeepMind, Darrell Etherington, TechCrunch, July 12, 2017, available from https://techcrunch.com/2017/07/12/microsoft-creates-an-ai-research-lab-t...

See the rest here:
Artificial Intelligence | Tools, Publications & Resources

Perfectly Imperfect: Coping With The Flaws Of Artificial Intelligence (AI) – Forbes

Perfectly imperfect

What is the acceptable failure rate of an airplane? Well, it is not zero no matter what how hard we want to believe otherwise. There is a number, and it is a very low number. When it comes to machines, computers, artificial intelligence, etc., they are perfectly imperfect. Mistakes will be made. Poor recommendations will occur. AI will never be perfect. That does not mean they do not provide value. People need to understand why machines may mistakes and set their beliefs accordingly. This means understanding the three key areas on why AI fails: implicit bias, poor data, and expectations.

The first challenge is implicit bias, which are the unconscious perceptions people have that cloud thoughts and actions. Consider, the recent protests on racial justice and police brutality and the powerful message that Black Lives Matter. The Forbes article AI Taking A Knee: Action To Improve Equal Treatment Under The Law is a great example of how implicit bias has played a role in the discrimination and just how hard (but not impossible) it is to use AI to reduce prejudice in our law enforcement and judicial systems. AI learns from people. If implicit bias is in the training, then the AI will learn this bias. Moreover, when the AI performs work, that work will reflect this bias even if the work is for social good.

Take for example the Allegheny Family Screening Tool. It is meant to predict which welfare children might be at risk from foster parent abuse. The initial rollout of this solution had some challenges though. The local Department of Human Services acknowledged that the tool might have racial and income bias. Triggers like neglect were often confused or misconstrued by associating foster parents who lived in poverty with inattention or mistreatment. Since learning of these problems, tremendous steps were taken to reduce the implicit bias in the screening tool. Elimination is much harder. When it comes to bias, how do people manage the unknown unknowns? How is social context addressed? What does right or fair behavior mean? If people cannot identify, define, and resolve these questions, then how will they teach the machine? This is a major driver AI will be perfectly imperfect because of implicit bias.

Coronavirus 2019 - ncov flu infection - 3D illustration

The second challenge is data. Data is the fuel for AI. The machine trains through ground truth (i.e. rules on how to make decisions, not the decisions themselves) and from lots of big data to learn the patterns and relationships within the data. If our data is incomplete or flawed, then AI cannot learn well. Consider COVID-19. John Hopkins, The COVID Tracking Project, U.S. Centers for Disease Control (CDC), and the World Health Organization all report different numbers. With such variation, it is very difficult for an AI to gleam meaningful patterns from the data let alone find those hidden insights. More challenging, what about incomplete or erroneous data? Imagine teaching an AI about healthcare but only providing data on womens health. That impedes how we can use AI in healthcare.

Then there is a challenge in that people may provide too much data. It could be irrelevant, unmeaningful, or even a distraction. Consider when IBM had Watson read the Urban Dictionary, and then it could not distinguish when to use normal language or to use slang and curse words. The problem got so bad that IBM had to erase the Urban Dictionary from Watsons memory. Similarly, an AI system needs to hear about 100 million words to become fluent in a language. However, a human child only seems to need around 15 million words to become fluent. This implies that we may not know what data is meaningful. Thus, AI trainers may actually focus on superfluous information that could lead the AI to waste time, or even worse, identify false patterns.

The third challenge is expectations. Even though humans make mistakes, people still expect machines to be perfect. In healthcare, experts have estimated that the misdiagnosis rate may be as high as 20%, which means potentially one out of five patients are misdiagnosed. Given this data as well as a scenario where an AI assisted diagnosis may have an error rate of one out of one hundred thousand, most people still prefer to see only the human doctor. Why? One of the most common reasons given is that the misdiagnosis rate of the AI is too high (even though it is much lower than a human doctor.) People expect AI to be perfect. Potentially even worse, people expect the human AI trainers to be perfect too.

On March 23, 2016, Microsoft launched Tay (Thinking About You), a Twitter bot. Microsoft had trained its AI to the level of language and interaction of a 19-year-old, American girl. In a grand social experiment, Tay was released to the world. 96,000 tweets later, Microsoft had to shut Tay down about 16 hours after launch because it had turned sexist, racist, and promoted Nazism. Regrettably, some individuals decided to teach Tay about seditious language to corrupt it. In conjunction, Microsoft did not think to teach Tay about inappropriate behavior so it had no basis (or reason) to know that something like inappropriate behavior and malicious intent might exist. The grand social experiment resulted in failure, and sadly, was probably a testament more about human society than the limitations of AI.

nobodys perfect

Implicit bias, poor data, and people expectations show that AI will never be perfect. It is not the magic bullet solution many people hope to have. AI can still do some extraordinary things for humans like restore mobility to a lost limb or improve food production while using less resources. People should not discount the value we can get. We should always remember: AI is perfectly imperfect, just like us.

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Perfectly Imperfect: Coping With The Flaws Of Artificial Intelligence (AI) - Forbes

What Makes Food Delivery Companies Bet Big on Artificial Intelligence and Machine Learning | Learn More in Quantzig’s Recent Article – Business Wire

LONDON--(BUSINESS WIRE)--Quantzig, a global data analytics and advisory firm that delivers actionable analytics solutions to resolve complex business problems, brings to you comprehensive insights into the benefits of machine learning and artificial intelligence for food delivery companies in its recent article.

Whats in it for you?

Talk to our analytics experts for comprehensive insights on how artificial intelligence and machine learning for food delivery industry is transforming the complete food and beverages industry.

After several years of restricted use and confinement to tech labs, today artificial intelligence and machine learning have become dominant focal points for businesses especially in the food delivery industry. Food delivery industry is immensely popular among the millennials due to the convenience involved in the usage. The increasing competition among food delivery industry players to improve customer retention rates and improve product quality has forced the companies to explore new ways of improvement, and this is where big data, artificial intelligence and machine learning for food delivery industry comes into the picture.

Request a FREE proposal to learn more about our customized machine learning for food industry.

According to Quantzigs artificial intelligence and machine learning experts, Food delivery industry players are now revolutionizing the food industry by leveraging artificial intelligence and machine learning to enhance their market reach and customer satisfaction rates.

Three Reasons Why Machine Learning for Food Delivery Industry is Important

1: Improve operational efficiency: Machine learning for food delivery industry helps to understand the customer behavior better and provide services as per their preferences. Artificial intelligence and machine learning is of great use when it come to analyze factors like the impact of temperature on food or the impact of market trends on consumption.

2: Enhance customer relationship: The rapid spread of artificial intelligence and machine learning in the food delivery industry have contributed significantly to the growing popularity of chatbots. These chatbots enable food delivery companies to enhance customer relationships. It is growing immensely popular due to its ability to drive better customer experiences.

3: Accurate delivery time estimates: Machine learning for food delivery industry helps to collect real-time data about traffic, and route plans and hence provides companies with an accurate estimation of the delivery time. Moreover, artificial intelligence and machine learning combined together can help in predicting the impact of these factors on food items and hence food delivery industry players can take preventive measures for food wastage.

Book a FREE solution demo to know how food delivery apps can leverage artificial intelligence and machine learning to evaluate their customers sentiments and take appropriate actions whenever required.

About Quantzig

Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal

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What Makes Food Delivery Companies Bet Big on Artificial Intelligence and Machine Learning | Learn More in Quantzig's Recent Article - Business Wire

Artificial Intelligence and the Fight Against COVID-19 – nesta

This report studies the levels, evolution, geography, knowledge base and quality of AI research in the COVID-19 mission field using a novel dataset taken from open preprints sites arXiv, bioRxiv and medRxiv, which we have enriched with geographical, topical and citation data.

Although there has been rapid growth in the levels of AI research to tackle COVID-19 since the beginning of the year, AI remains underrepresented in this area compared to its presence in research outside of COVID-19. So far in 2020, 7.1 per cent of research on COVID-19 references AI, while 12 per cent of research on topics outside COVID-19 references it. After growing rapidly earlier in the year, the share of AI papers in COVID-19 research has stagnated in recent weeks.

More than a third of publications to tackle COVID-19 involve predictive analyses of patient data and in particular medical scans. AI is also being deployed to analyse social media data, predict the spread of the disease and develop biomedical applications.

China, the US, the UK, India and Canada are the global leaders in the development of AI applications to tackle COVID-19 research, accounting for 62 per cent of the institutional participations for which we have geographical data. China in particular is overrepresented in COVID-19 AI research. We have also identified a substantial number of publications involving institutions that we are unable to match with the global research institution database we are using. This is consistent with the idea that new actors are entering the COVID-19 mission field.

AI and non-AI researchers working in COVID-19 tend to draw on different bodies of knowledge. AIs share of citations to computer science is five times higher than outside and its share of citations to medicine is a third lower. These differences hold, even after we control for the topic within COVID-19 that different publications focus on .

In general, AI papers to tackle COVID-19 tend to receive less citations than other papers in the same topic. The population of AI researchers active in the COVID-19 mission field also tends to have a less established track record proxied through the citations they have received in recent years. This result holds when we compare researchers working in the same topics, suggesting that it is not simply driven by variation in the citation behaviours of different communities and disciplines.

Our analysis highlights the velocity with which research communities including AI researchers are mobilising to tackle the COVID-19 pandemic. We find many opportunities to apply powerful AI algorithms to prevent, diagnose and treat the virus. At the same time, deep learning algorithms reliance on big datasets, difficulties interpreting their findings, and a disconnect between AI researchers and relevant bodies of knowledge in the medical and biological sciences may limit the impact of AI in the fight with COVID-19. The persistent underrepresentation of AI research in the COVID-19 field we evidence, and its focus on computer vision analyses that play to the strengths of current algorithms, but require substantial investments in hardware and changing how hospitals work, are consistent with the notion that AIs may play a limited role tackling this pandemic.

There is also the risk that researchers facing low barriers to entry into the field may produce low-quality contributions making it harder to find valuable studies and discourage interdisciplinary contributions that could take longer to develop. Our finding that AI research tends to be less cited than other research, even inside the same publication topics, and that AI researchers entering the field have a weaker track record on average than others, lends some support to these concerns.

In the shorter term, creating bigger higher-quality open datasets related to COVID-19 could make it easier to deploy state-of-the-art deep learning algorithms. Spurring interdisciplinary collaborations, bringing together AI researchers and subject experts, may help to prioritise those AI applications with the greatest relevance and value. It might also reduce the risk of AI imperialism; where AI researchers ignore relevant bodies of knowledge about the complex biological and social systems where their techniques will be applied, reducing their value and creating unintended consequences. We also need technological and social solutions for the challenge of navigating a vast and fast-growing body of research of uncertain quality. Going forward, research funders should encourage the development of AI algorithms that are easier to deploy in small-data, high-stakes domains.

Novel data sources and methods, such as those we have used in our analysis, can play an important role in informing these strategies.

The data set used in this report is open for other researchers to analyse and build on.

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Artificial Intelligence and the Fight Against COVID-19 - nesta

InfoSystems To Host 2 Virtual Workshops Related To Artificial Intelligence In Business – The Chattanoogan

As artificial intelligence spreads into more industries, InfoSystems, an IBM Platinum Business Partner, is committed to preparing the local business community to utilize the technology in a meaningful way, said officials.

As part of this mission, they are hosting two free virtual workshops on Wednesday and Thursday. While both will focus on artificial intelligence and how the technology is evolving, the two workshops will have slightly different messaging.

It is important to us that we continue to find ways to invest in the business community, said Keith Hales, chief operating officer at InfoSystems and event host. Even in the face of very real health and economic challenges, businesses still must find ways to improve, innovate, and ultimately make enough profit to keep the doors open.

The first workshop will take place from 11:30 a.m.-1 p.m. on Wednesday. It will provide foundational knowledge about artificial intelligence, a technology that has the power to help companies quickly gain competitive insights. During this virtual workshop, participants will learn steps they can take to get their existing technology ready for AI projects in the future.

LinkedIn event link: https://www.linkedin.com/events/6669583402284408832/Eventbrite event link: https://www.eventbrite.com/e/106093961896

The second workshop will take place from 11:30 a.m.-1 p.m. on Thursday. It will elaborate on artificial intelligence by teaching ways in which businesses can effectively store, manage, and secure their data. Participants will learn actionable solutions that can be deployed to protect their companys data, as well as how to prepare to use that data with AI applications and other new technologies.

LinkedIn event link: https://www.linkedin.com/events/6669594794299277312/Eventbrite event link: https://www.eventbrite.com/e/106104379054

There are very few instances in history in which a new technology will create the type of disruption that artificial intelligence is going to, said Josh Davis, vice president of Marketing at InfoSystems. We feel it's important for businesses in our community to have the information they need to get prepared for this.

While these workshops include technical topics, they are really a how-to guide intended to help businesses considering these technologies, said Mr. Hales. Our job is to educate and provide the best technology options available. Ultimately, if we help businesses make better technology decisions, we all win.

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InfoSystems To Host 2 Virtual Workshops Related To Artificial Intelligence In Business - The Chattanoogan

Burden of COVID-19 on the Market & Rehabilitation Plan | Global Artificial Intelligence (AI) Market In Retail Sector 2019-2023 | The Increased…

LONDON--(BUSINESS WIRE)--Technavio has been monitoring the global artificial intelligence (AI) market in retail sector and it is poised to grow by USD 14.05 billion during 2019-2023, progressing at a CAGR of 35% during the forecast period. The report offers an up-to-date analysis regarding the current market scenario, latest trends and drivers, and the overall market environment.

Although the COVID-19 pandemic continues to transform the growth of various industries, the immediate impact of the outbreak is varied. While a few industries will register a drop in demand, numerous others will continue to remain unscathed and show promising growth opportunities. Technavios in-depth research has all your needs covered as our research reports include all foreseeable market scenarios, including pre- & post-COVID-19 analysis. Download a Free Sample Report

The market is fragmented, and the degree of fragmentation will accelerate during the forecast period. IBM Corp., Intel Corp., Microsoft Corp., NVIDIA Corp., and Oracle Corp are some of the major market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

Buy 1 Technavio report and get the second for 50% off. Buy 2 Technavio reports and get the third for free.

View market snapshot before purchasing

The increased efficiency of operations has been instrumental in driving the growth of the market.

Technavio's custom research reports offer detailed insights on the impact of COVID-19 at an industry level, a regional level, and subsequent supply chain operations. This customized report will also help clients keep up with new product launches in direct & indirect COVID-19 related markets, upcoming vaccines and pipeline analysis, and significant developments in vendor operations and government regulations. https://www.technavio.com/report/global-artificial-intelligence-ai-market-in-retail-sector-industry-analysis

Artificial Intelligence (AI) Market in Retail Sector 2019-2023: Segmentation

Artificial Intelligence (AI) Market in Retail Sector is segmented as below:

To learn more about the global trends impacting the future of market research, download a free sample: https://www.technavio.com/talk-to-us?report=IRTNTR31763

Artificial Intelligence (AI) Market in Retail Sector 2019-2023: Scope

Technavio presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources. The artificial intelligence (AI) market in retail sector report covers the following areas:

This study identifies the increased applications in e-commerce as one of the prime reasons driving the artificial intelligence (AI) market growth in retail sector during the next few years.

Technavio suggests three forecast scenarios (optimistic, probable, and pessimistic) considering the impact of COVID-19. Technavios in-depth research has direct and indirect COVID-19 impacted market research reports.

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Artificial Intelligence (AI) Market in Retail Sector 2019-2023: Key Highlights

Table of Contents:

PART 01: EXECUTIVE SUMMARY

PART 02: SCOPE OF THE REPORT

PART 03: MARKET LANDSCAPE

PART 04: MARKET SIZING

PART 05: FIVE FORCES ANALYSIS

PART 06: MARKET SEGMENTATION BY APPLICATION

PART 07: CUSTOMER LANDSCAPE

PART 08: GEOGRAPHIC LANDSCAPE

PART 09: DECISION FRAMEWORK

PART 10: DRIVERS AND CHALLENGES

PART 11: MARKET TRENDS

PART 12: VENDOR LANDSCAPE

PART 13: VENDOR ANALYSIS

PART 14: APPENDIX

PART 15: EXPLORE TECHNAVIO

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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Burden of COVID-19 on the Market & Rehabilitation Plan | Global Artificial Intelligence (AI) Market In Retail Sector 2019-2023 | The Increased...