The Birth of Artifical Intelligence

Artificial intelligence (A.I.) is said to have had its humble beginning in 1956 at a summer-long conference called the Dartmouth Summer Research Project on Artificial Intelligence. The purpose of the conference was to investigate which aspects of human learning could be programmed into thinking machines, the precursor to computers. The intent was to find ways for these thinking machines to solve problems and learn from their mistakes, just as humans do.

Since then, Artificial intelligence has not so quietly been the engine behind transformative changes in how people think, make buying decisions, and relate to one another in a way while redefining the very definition of community, friendship and social discourse.

AI is disrupting the status quo across a broad cross section of industries by demonstrating its superiority and effectiveness as a powerful data mining, pattern recognition and forecasting tool that can tackle challenges that no human or other mathematical-based technology can achieve.

Siri (Apple) and Alexa (Amazon), have already worked their way into our daily lives as A.I. personal assistants. Social media platforms like Facebook have helped warm up the public to this disruptive technology that is reshaping nearly every industry and government worldwide.

Now, with more than 60 years of progress, this transformative technology is poised to make the difference between growth and decline for businesses worldwide as it disrupts and transforms practically every aspect of the human experience touched by technology.

Artificial intelligence, as its been understood to date by the public, conjures up fearful images of armies of robots rising up and challenging humankind for supremacy in intelligence as well as in physical prowess. Taken to its logical extreme this doomsday perspective of this incredible predictive technology has been widely promoted over the years in science fiction books and in big screen horror movies. While such fears are not entirely unfounded, they are, at this point in history, quite premature given the current state-of-the-art in artificial intelligence.

Yet, despite these concerns and even fear of where this technology will take us over the next century, artificial intelligence has, not so quietly, been the engine behind transformative changes in how people think, make buying decisions, and relate to one another in a way which has been redefining the very definition of community, friendship and every other aspect of social discourse. These changes to date have been mainly due to the application of A.I. to such areas as facial recognition and speech recognition, within the overall general arena known as pattern recognition.

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Artificial Intelligence Technology | VantagePoint

Directorate General Human Rights and Rule of Law, Council of Europe

The second plenary meeting of the Ad Hoc Committee on Artificial Intelligence (CAHAI) will be held from 6 to 8 July 2020, bringing together representatives of the 47 Council of Europe member states, observer states (Canada, USA, Holy See, Japan, Mexico) as well as civil society, academia and the Council of Europe's Internet partners.

The CAHAI observer group is expanding with the participation for the first time of Israel and 12 new stakeholders. Other international organisations (EU, OECD, UNESCO) will also contribute to CAHAIs work.

CAHAI members will make concrete proposals on the feasibility study of a future legal framework on artificial intelligence (AI) based on human rights, democracy and the rule of law. In this connection, they will address issues such as the mapping of legal instruments applicable to AI and the opportunities and risks arising from the design, development and application of AI on human rights, rule of law and democracy, which have already been subject of a preliminary analysis.

Other issues such the scope and main elements of the above-mentioned legal framework will also be discussed.

This will provide the necessary impetus for the preparation of the first draft of the feasibility study, which will be presented at the CAHAI plenary meeting in December 2020.

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Second plenary meeting of the Ad Hoc Committee on Artificial Intelligence (CAHAI) - Council of Europe

Volkswagen is looking to boost its production by as much as 30 per cent in next five years by using Artificial Intelligence at its facilities. The Industrial Computer Vision AI technology will help the carmaker in image recognition processes and speed up production time by reducing manual interventions

The process extracts information from optical data, such as the real environment at the plant, which it then evaluates using artificial intelligence (AI). The procedure is similar to the human capability of recognising, processing and analysing images. Volkswagen has been working with this technology for several years and is now intensifying its efforts.

The first application, which is to be rolled out via the new Volkswagen Industrial Cloud throughout the Group next year, is currently being tested by Porsche in Leipzig. The application functions as follows: several labels are attached to each vehicle produced, for example with vehicle information or notes on airbags. Many of these labels contain country-specific information and are written in the customers language. The proper application of these labels is ensured by Computer Vision.

At the Porsche plant in Leipzig, an employee on the production line now scans the vehicle identification number to ensure clear identification of the vehicle. Photos are taken of each label attached to the car. The app checks the images to ensure that the labels have the correct content and are written in the appropriate language on a real-time basis and provides the production line employee with feedback on whether everything is correct. This saves several minutes per vehicle.

Another solution currently being prepared for use throughout the Group comes from Ingolstadt, where Audi uses it for quality testing at the press shop. Cameras combined with software based on machine learning detect the finest cracks and defects in components.

Volkswagen has set up a team of about 60 Computer Vision experts for the further development of the technology and the evaluation of new utilisation possibilities. In addition to the use of the technology in production, Volkswagen plans applications along the entire value stream, for example in sales and after-sales. For development work on the optical procedure, Volkswagen is recruiting experts for this area in Berlin, Dresden, Munich and Wolfsburg. In addition, the Group continues to build up its skills in the fields of camera technology, machine learning and the operation of Computer Vision solutions.

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How Artificial Intelligence will help Volkswagen boost production by 30 per cent - Hindustan Times

Jul 4th 2020

Artificial intelligence is an oxymoron (Technology quarterly, June 13th). Intelligence is an attribute of living things, and can best be defined as the use of information to further survival and reproduction. When a computer resists being switched off, or a robot worries about the future for its children, then, and only then, may intelligence flow.

I acknowledge Richard Suttons bitter lesson, that attempts to build human understanding into computers rarely work, although there is nothing new here. I was aware of the folly of anthropomorphism as an AI researcher in the mid-1980s. We learned to fly when we stopped emulating birds and studied lift. Meaning and knowledge dont result from symbolic representation; they relate directly to the visceral motives of survival and reproduction.

Great strides have been made in widening the applicability of algorithms, but as Mr Sutton says, this progress has been fuelled by Moores law. What we call AI is simply pattern discovery. Brilliant, transformative, and powerful, but just pattern discovery. Further progress is dependent on recognising this simple fact, and abandoning the fancy that intelligence can be disembodied from a living host.

ROB MACDONALDRichmond, North Yorkshire

I agree that machine learning is overhyped. Indeed, your claim that such techniques are loosely based on the structure of neurons in the brain is true of neural networks, but these are just one type among a wide array of different machine- learning methods. In fact, machine learning in some cases is no more than a rebranding of existing processes. If by machine learning we simply mean building a model using large amounts of data, then good old ordinary least squares (line of best fit) is a form of machine learning.

TOM ARMSTRONGToronto

The scope of your research into green investing was too narrow to condemn all financial services for their woolly thinking (Hotting up, June 20th). You restricted your analysis to microeconomic factors and to the ability of investors to engage with companies. It overlooked the bigger picture: investors can also shape the macro environment by structured engagement with the system itself.

For example, the data you used largely originated from the investor-led Carbon Disclosure Project (for which we hosted the first ever meeting, nearly two decades ago). In addition, investors have also helped shape sustainable-finance plans in Britain, the EU and UN. Investors also sit on the industry-led Taskforce on Climate-related Financial Disclosure, convened by the Financial Stability Board, which has proved effective.

It is critical that governments apply a meaningful carbon price. But if we are to move money at the pace and scale required to deal with climate risk, governments need to reconsider the entire architecture of markets. This means focusing a wide-angled climate lens on prudential regulation, listing rules, accounting standards, investor disclosure standards, valuation conventions and stewardship codes, as well as building on new interpretations of legal fiduciary duty. This work is done most effectively in partnership with market participants. Green-thinking investors can help.

STEVE WAYGOODChief responsible investment officerAviva InvestorsLondon

Estimating indirectly observable GDP in real time is indeed a hard job for macro-econometricians, or wonks, as you call us (Crisis measures, May 30th). Most of the components are either highly lagged, as your article mentioned, or altogether unobservable. But the textbook definition of GDP and its components wont be changing any time soon, as the reader is led to believe. Instead what has always and will continue to change are the proxy indicators used to estimate the estimate of GDP.

MICHAEL BOERMANWashington, DC

Reading Lexingtons account of his garden adventures (June 20th) brought back memories of my own experience with neighbours in Twinsburg, Ohio, in the late 1970s. They also objected to vegetables growing in our front yard (the only available space). We were doing it for the same reasons as Lexington: pleasure, fresh food to eat, and a learning experience for our young children. The neighbours, recently arrived into the suburban middle class, saw it as an affront. They no longer had to grow food for their table. They could buy it at the store and keep it in the deep freeze. Our garden, in their face every day, reminded them of their roots in Appalachian poverty. They called us hillbillies.

Arthur C. Clarke once wrote: Any sufficiently advanced technology is indistinguishable from magic. Our version read, Any sufficiently advanced lifestyle is indistinguishable from hillbillies.

PHILIP RAKITAPhiladelphia

Bartleby (May 30th) thinks the benefits of working from home will mean that employees will not want to return to the office. I am not sure that is the case for many people. My husband is lucky. He works for a company that already expected its staff to work remotely, so had the systems and habits in place. He has a spacious room to work in, with an adjustable chair, large monitor and a nice view. I do not work so he is not responsible for child care or home schooling.

Many people are working at makeshift workspaces which would make an occupational therapist cringe. Few will have a dedicated room for their home office, so their work invades their mental and physical space.

My husband has noticed that meetings are being set up both earlier and later in the day because there is an assumption that, as people are not commuting, it is fine to extend their work day. Colleagues book a half-hour meeting instead of dropping by someones desk to ask a quick question. Any benefit of not commuting is lost. My husband still struggles to finish in time to have dinner with our children. People with especially long commutes now have more time, but even that was a change of scenery and offered some incidental exercise.

JENNIFER ALLENLondon

As Bartleby pointed out, the impact of pandemic working conditions wont be limited to the current generation. By exacerbating these divides, will covid-19 completely guarantee a future dominated by the baby-Zoomers?

MALCOLM BEGGTokyo

The transition away from the physical office engenders a lackadaisical approach to the work day for many workers. It brings to mind Ignatius Reillys reasoning for his late start at the office from A Confederacy of Dunces:

I avoid that bleak first hour of the working day during which my still sluggish senses and body make every chore a penance. I find that in arriving later, the work which I do perform is of a much higher quality.

ROBERT MOGIELNICKIArlington, Virginia

This article appeared in the Letters section of the print edition under the headline "On artificial intelligence, green investing, GDP, gardens, working from home"

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Letters to the editor - The Economist

In 2018, Congress established the National Security Commission on Artificial Intelligence (NSCAI)a temporary, independent body tasked with reviewing the national security implications of artificial intelligence (AI). But two years later, the commissions activities remain little known to the public. Critics have charged that the commission has conducted activities of interest to the public outside of the public eye, only acknowledging that meetings occurred after the fact and offering few details on evolving commission decision-making. As one commentator remarked, Companies or members of the public interested in learning how the Commission is studying AI are left only with the knowledge that appointed people met to discuss these very topics, did so, and are not yet releasing any information about their recommendations.

That perceived lack of transparency may soon change. In June, the U.S. District Court for the District of Columbia handed down its decision in Electronic Privacy Information Center v. National Security Commission on Artificial Intelligence, holding that Congress compelled the NSCAI to comply with the Federal Advisory Committee Act (FACA). Under FACA, the commission must hold open meetings and proactively provide records and other materials to the public. This decision follows a ruling from December 2019, holding that the NSCAI must also provide historical documents upon request under the Freedom of Information Act (FOIA). As a result of these decisions, the public is likely to gain increased access to and insight into the once-opaque operations of the commission.

Lawmakers established the NSCAI in the John S. McCain National Defense Authorization Act (NDAA) for fiscal 2019 1051, which tasked the commission with consider[ing] the methods and means necessary to advance the development of artificial intelligence, machine learning, and associated technologies to comprehensively address the national security and defense needs of the United States. The commissions purview includes an array of issues related to the implications and uses of artificial intelligence and machine learning for national security and defense, including U.S. competitiveness and leadership, research and development, ethics, and data standards.

The NSCAI is currently chaired by Eric Schmidt, the former executive chairman of Googles parent company, Alphabet. The commissions 15 membersappointed by a combination of Congress, the secretary of defense and the secretary of commercereceive classified and unclassified briefings, meet in working groups and engage with industry. They report their findings and recommendations to the president and Congress, including in an annual report.

The Electronic Privacy Information Center (EPIC), a research center focused on privacy and civil liberties issues in the digital age, submitted a request to the NSCAI in September 2019, seeking access to upcoming meetings and records prepared by the commission under FACA and FOIA. In the six-month period prior to the request, the NSCAI held more than a dozen meetings and received over 100 briefings, according to EPIC. At the time it filed the lawsuit, EPIC noted that the commissions first major report was also one month overdue for release. When the commission did not comply with the requests under FOIA and FACA, EPIC brought suit under the two laws.

EPICs complaint alleged that the NSCAI had conducted its operations opaquely in its short lifespan. Since its establishment, the commission has operated almost entirely in secret with meetings behind closed doors[,] and has failed to publish or disclose any notices, agendas, minutes, or materials. If Congress had intended the NSCAI to comply with FOIA and FACA, such activity would not satisfy the statutes requirements. Given the potential implications of federal artificial intelligence decisions for privacy, cybersecurity, human rights, and algorithmic bias, EPIC argued that [p]ublic access to the records and meetings of the AI Commission is vital to ensure government transparency and democratic accountability. The complaint also noted the potential ramifications of commission activities for the government, private sector, and public, as well as the importance of artificial intelligence safeguards in the national security context due to limited public oversight. According to EPIC, increasing public participation would permit greater input into the development of national AI policy by those whose privacy and data security could potentially be affected.

The U.S. District Court for the District of Columbia addressed EPICs FOIA claim in a December 2019 decision. FOIA requires agencies to disclose their records to a party upon request, barring exemptions (including for information classified to protect national security). EPIC alleged that the NSCAI failed to uphold its obligations under FOIA to process FOIA requests in a timely fashion; to process EPICs FOIA requests in an expedited manner, in accordance with EPICs claims of urgency; and to make available for public inspection and copying its records, reports, transcripts, minutes, appendixes, working papers, drafts, studies, agenda, or other documents. The commission, which at the time did not have a FOIA processing mechanism in place or other pending FOIA requests, argued that it was not an agency subject to FOIA.

The courts inquiry centered on whether the NSCAI is an agency under FOIA. Comparing the language establishing the NSCAI with FOIAs definition of agency, the court held that the NSCAI is subject to FOIA. In his decision, District Judge Trevor McFadden noted that Congress could have hardly been clearer. As a result, since that time, the commission has had to produce historical documents in response to FOIA requests.

FACA, by contrast, applies forward-looking requirements specifically to federal advisory committees. These mandates include requiring committees to open meetings to the public and announce them in the Federal Register, and to make reports, transcripts and other commission materials publicly available. The measures aim to inform the public about and invite public engagement with the committees that provide expertise to the executive branch. EPIC alleged that the NSCAI violated FACA by failing to hold open meetings and provide notice of them, and by failing to make records available to the public. EPIC sought mandamus relief pursuant to the alleged FACA violations.

In its June decision, the district court ruled that FACA applies to the NSCAI. The commission had filed a motion to dismiss the FACA claims, arguing that it could not be subject to both FOIA and FACA. Since the court had previously held the NSCAI to be an agency for purposes of FOIA, the commission reasoned that it could not simultaneously be an advisory committee under FACA. District Judge McFadden disagreed. Invoking the Roman God Januss two facesone forward-looking and the other backward-facinghe wrote, [L]ike Janus, the Commission does indeed have two faces, and ... Congress obligated it to comply with FACA as well as FOIA. The court could not identify a conflict between the requirements of the two statutes, despite differences in their obligations and exceptions. Rather, it noted that if such conflicts arise, it will be incumbent on the parties and the Court to resolve any difficulties. The court dismissed additional claims under the Administrative Procedure Act (APA) for lack of subject matter jurisdiction, as it determined that the commission is not an agency under the APA definition.

The courts decision turned on whether the NSCAI is an advisory committee subject to FACA. The court determined that the statutory text of the 2019 NDAA establishing the NSCAI fit[s] the [FACA] definition of advisory committee like a glove. Furthermore, turning to the full text of the 2019 NDAA, the court noted that the law contains at least two instances in which it explicitly exempts a government body from FACA. The court read the 2019 NDAA as silent when FACA applies and explicit when FACA does not apply. Given Congresss silence on the applicability of FACA to the NSCAI in the 2019 NDAAand again in the 2020 NDAAthe court reasoned that Congress intended the NSCAI to be subject to FACA.

In determining the NSCAI to be subject to FACA, in addition to FOIA, the court has compelled the commission to adopt a more transparent operating posture going forward. Since the December 2019 decision on FOIA, the NSCAI has produced a number of historical records in response to FOIA requests. The recent ruling on FACA grounds requires the NSCAI to hold open meetings, post notice of meetings in advance and make documents publicly available. As a result, the commissions process of compiling findings and developing recommendations for government action related to artificial intelligence and machine learning will likely become more accessible to the public.

The two court decisions come in time to have a noticeable impact on the remaining term of the temporary commission. While the NSCAI was previously due to disband later in 2020, the NDAA for fiscal 2020 1735 extended the commissions lifespan by one year, to October 1, 2021. Citing federal budgetary timelines and the pace of AI development, the commission released its first set of recommendations in March 2020 and expressed its intent to publish additional recommendations on a quarterly basis thereafter. The commission is due to submit its final report to Congress by March 1, 2021. As the NSCAI prepares to enter its final year of operations and develop its closing recommendations, the public will have a clearer window into the commissions work.

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Increasing Transparency at the National Security Commission on Artificial Intelligence - Lawfare