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Driving Tomorrow: Self-Driving Cars and its (legal) future

Dr. Andreas Eustacchio

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“The highly intriguing theory – supported by the extensive geological evidences including the bacteriological analysis of deep-laying hydrocarbons – about the a biotic nature of oil and its practically infinite recreation in the lower geological formations of earth was presented some 25 years ago. These findings were quickly dismissed, and the theory itself largely ignored and forgotten. The same happened with the highly elaborate plans of Nikola Tesla to exploit a natural geo-electrical phenomenon for the wireless transfers of high energy for free. Why? Infinity eliminates the premium of deeper psychologisation, as it does not necessitate any emotional attachment – something abundantly residing in nature cannot efficiently mobilize our present societies…”

Following the lines from the seminar work of prof. Anis H. Bajrektarevic on Energy, Technology and Geopolitics, let us present an interesting take on the E-cars, similar driverless technologies and its legal implications that will mark our near future.

Self-driving cars react in a split second: quicker than even the most attentive driver. Self-driving cars don’t get tired, they don’t lose concentration or become aggressive; they’re not bothered by everyday problems and thoughts; they don’t get hungry or develop headaches. Self-driving cars don’t drink alcohol or drive under the influence of drugs. In short, human error, the number one cause of road traffic accidents, could be made a thing of the past in one fell swoop if manual driving were to be banned immediately. Is that right? It would be, if there hadn’t recently been reports about two deaths, one during the test drive for a self-driving car (UBER) and one while a semi-autonomous vehicle was driving on a motorway and using its lane assist system (Tesla), both of which regrettably occurred in the USA in March 2018. In Tesla’s case it seems that the semi-autonomous driving assistant was switched off at the moment of the accident.

Around the globe, people die every day due to careless driving, with around 90% of all accidents caused by human error and just a small percentage due to a technical fault related to the vehicle. Despite human error, we have not banned driving on these grounds. Two accidents with fatal consequences involving autonomous vehicles being test-driven have attracted the full glare of the media spotlight, and call into question the technical development of a rapidly progressing industry. Are self-driving cars now just hype, or a trend that cannot be contained, despite every additional human life that is lost as a result of mistakes made by self-driving technology?

The legal side

For many, the thought that fully autonomous vehicles (a self-driving car without a driver) might exist in the future is rather unsettling. The two recent deaths in the USA resulting from (semi-) autonomous cars have, rather, may cause fear for others. From a legal perspective, it makes no difference whatsoever for the injured party whether the accident was caused by a careless human or technology that was functioning inadequately. The reason for the line drawn between the two, despite this fact, is probably that every human error represents a separate accident, whereas the failure or malfunction of technology cannot be seen as a one-off: rather, understandably and probably correctly, it is viewed as a system error or series error caused by a certain technology available at a particular point in time.

From a legal angle, a technical defect generally also represents a design defect that affects the entire run of a particular vehicle range. Deaths caused by software malfunctions cause people to quickly lose trust in other vehicles equipped with the same faulty software. Conversely, if a drunk driver injures or kills another road user, it is not assumed that the majority of other drivers (or all of them) could potentially cause accidents due to the influence of alcohol.

The desirability side

The fundamental question for all technological developments is this: do people want self-driving cars?

When we talk of self-driving (or autonomous) vehicles, we mean machines guided by computers. On-board computers are common practice in aviation, without the pilot him- or herself flying the plane – and from a statistical point of view, airplanes are the safest mode of transport. Couldn’t cars become just as safe? However, a comparison between planes and cars cannot be justified, due to the different user groups, the number of cars driven every day, and the constantly imminent risk of a collision with other road users, including pedestrians.

While driver assistance systems, such as lane assist, park assist or adaptive cruise control, can be found in many widespread models and are principally permitted and allowed in Europe, current legislation in Europe and also Austria only permits (semi-) autonomous vehicles to be used for test purposes. Additionally, in Austria these test drives can, inter alia, only take place on motorways or with minibuses in an urban environment following specially marked routes (cf. the test drives with minibuses in the towns of Salzburg and Velden). Test drives have been carried out on Austria’s roads in line with particular legal requirements for a little more than a year, and it has been necessary to have a person in the vehicle at all times. This person must be able to intervene immediately if an accident is on the horizon, to correct wrong steering by the computer or to get the vehicle back under (human) control.

Indeed, under the legislation in the US states that do permit test drives, people still (currently) need to be inside the car (even before the two accidents mentioned above, California had announced a law that would have made it no longer necessary to have a person in the vehicle). As a result, three questions arise regarding the UBER accident which occurred during a test drive in the US state of Arizona, resulting in a fatal collision with a cyclist:

  1. Could the person who was inside the vehicle to control it for safety reasons have activated the emergency brake and averted the collision with the cyclist who suddenly crossed the road?
  2. Why did the sensors built into the car not recognize the cyclist in time?
  3. Why did the vehicle not stick to the legal speed limit?

Currently, driving systems are being tested in Europe and the USA. In the USA, this can take place on national roads and, contrary to European legislation, also on urban streets. As long as we are still in the test phase we cannot talk of technically proven, let alone officially approved, driving systems. The technical development of self-driving cars, however, has already made it clear that legal responsibility is shifting away from the driver and towards vehicle manufacturers and software developers.

Our Prospects

Whether, and when, self-driving cars could become an everyday phenomenon is greatly dependent on certain (future) questions:

  • Are we right to expect absolute safety from self-driving cars?
  • What decisions should self-driving cars make in the event that one life can only be saved at the cost of another?
  • How should this dilemma be resolved?

If artificial intelligence (AI) and self-learning systems could also be included within the technology for self-driving cars, vehicles of this type might possibly become one day “humanoid robots on four wheels”, but they could not be compared to a human being with particular notions of value and morality. If every individual personally bears responsibility for their intuitive behavior in a specific accident situation, the limits of our legal system are laid bare if algorithms using huge quantities of data make decisions in advance for a subsequent accident situation: these decisions can no longer be wholly ascribed to a particular person or software developer if a self-driving car is involved. It will be our task as lawyers to offer legal support to legislators as they attempt to meet these challenges.

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The Artificial Intelligence Race: U.S. China and Russia

Ecatarina Garcia

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Artificial intelligence (AI), a subset of machine learning, has the potential to drastically impact a nation’s national security in various ways. Coined as the next space race, the race for AI dominance is both intense and necessary for nations to remain primary in an evolving global environment. As technology develops so does the amount of virtual information and the ability to operate at optimal levels when taking advantage of this data. Furthermore, the proper use and implementation of AI can facilitate a nation in the achievement of information, economic, and military superiority – all ingredients to maintaining a prominent place on the global stage. According to Paul Scharre, “AI today is a very powerful technology. Many people compare it to a new industrial revolution in its capacity to change things. It is poised to change not only the way we think about productivity but also elements of national power.”AI is not only the future for economic and commercial power, but also has various military applications with regard to national security for each and every aspiring global power.

While the U.S. is the birthplace of AI, other states have taken a serious approach to research and development considering the potential global gains. Three of the world’s biggest players, U.S., Russia, and China, are entrenched in non-kinetic battle to out-pace the other in AI development and implementation. Moreover, due to the considerable advantages artificial intelligence can provide it is now a race between these players to master AI and integrate this capability into military applications in order to assert power and influence globally. As AI becomes more ubiquitous, it is no longer a next-generation design of science fiction. Its potential to provide strategic advantage is clear. Thus, to capitalize on this potential strategic advantage, the U.S. is seeking to develop a deliberate strategy to position itself as the permanent top-tier of AI implementation.

Problem

The current AI reality is near-peer competitors are leading or closing the gap with the U.S. Of note, Allen and Husain indicate the problem is exacerbated by a lack of AI in the national agenda, diminishing funds for science and technology funding, and the public availability of AI research. The U.S. has enjoyed a technological edge that, at times, enabled military superiority against near-peers. However, there is argument that the U.S. is losing grasp of that advantage. As Flournoy and Lyons indicate, China and Russia are investing massively in research and development efforts to produce technologies and capabilities “specifically designed to blunt U.S. strengths and exploit U.S. vulnerabilities.”

The technological capabilities once unique to the U.S. are now proliferated across both nation-states and other non-state actors. As Allen and Chan indicate, “initially, technological progress will deliver the greatest advantages to large, well-funded, and technologically sophisticated militaries. As prices fall, states with budget-constrained and less technologically-advanced militaries will adopt the technology, as will non-state actors.” As an example, the American use of unmanned aerial vehicles in Iraq and Afghanistan provided a technological advantage in the battle space. But as prices for this technology drop, non-state actors like the Islamic State is making noteworthy use of remotely-controlled aerial drones in its military operations. While the aforementioned is part of the issue, more concerning is the fact that the Department of Defense (DoD) and U.S. defense industry are no longer the epicenter for the development of next-generation advancements. Rather, the most innovative development is occurring more with private commercial companies. Unlike China and Russia, the U.S. government cannot completely direct the activities of industry for purely governmental/military purposes. This has certainly been a major factor in closing the gap in the AI race.

Furthermore, the U.S. is falling short to China in the quantity of studies produced regarding AI, deep-learning, and big data. For example, the number of AI-related papers submitted to the International Joint Conferences on Artificial Intelligence (IJCAI) in 2017 indicated China totaled a majority 37 percent, whereas the U.S. took third position at only 18 percent. While quantity is not everything (U.S. researchers were awarded the most awards at IJCAI 2017, for example), China’s industry innovations were formally marked as “astonishing.”For these reasons, there are various strategic challenges the U.S. must seek to overcome to maintain its lead in the AI race.

Perspectives

Each of the three nations have taken divergent perspectives on how to approach and define this problem. However, one common theme among them is the understanding of AI’s importance as an instrument of international competitiveness as well as a matter of national security. Sadler writes, “failure to adapt and lead in this new reality risks the U.S. ability to effectively respond and control the future battlefield.” However, the U.S. can longer “spend its way ahead of these challenges.” The U.S. has developed what is termed the third offset, which Louth and Taylor defined as a policy shift that is a radical strategy to reform the way the U.S. delivers defense capabilities to meet the perceived challenges of a fundamentally changed threat environment. The continuous development and improvement of AI requires a comprehensive plan and partnership with industry and academia. To cage this issue two DOD-directed studies, the Defense Science Board Summer Study on Autonomy and the Long-Range Research and Development Planning Program, highlighted five critical areas for improvement: (1) autonomous deep-learning systems,(2) human-machine collaboration, (3) assisted human operations, (4) advanced human-machine combat teaming, and (5) network-enabled semi-autonomous weapons.

Similar to the U.S., Russian leadership has stated the importance of AI on the modern battlefield. Russian President Vladimir Putin commented, “Whoever becomes the leader in this sphere (AI) will become the ruler of the world.” Not merely rhetoric, Russia’s Chief of General Staff, General Valery Gerasimov, also predicted “a future battlefield populated with learning machines.” As a result of the Russian-Georgian war, Russia developed a comprehensive military modernization plan. Of note, a main staple in the 2008 modernization plan was the development of autonomous military technology and weapon systems. According to Renz, “The achievements of the 2008 modernization program have been well-documented and were demonstrated during the conflicts in Ukraine and Syria.”

China, understanding the global impact of this issue, has dedicated research, money, and education to a comprehensive state-sponsored plan.  China’s State Council published a document in July of 2017 entitled, “New Generation Artificial Intelligence Development Plan.” It laid out a plan that takes a top-down approach to explicitly mapout the nation’s development of AI, including goals reaching all the way to 2030.  Chinese leadership also highlights this priority as they indicate the necessity for AI development:

AI has become a new focus of international competition. AI is a strategic technology that will lead in the future; the world’s major developed countries are taking the development of AI as a major strategy to enhance national competitiveness and protect national security; intensifying the introduction of plans and strategies for this core technology, top talent, standards and regulations, etc.; and trying to seize the initiative in the new round of international science and technology competition. (China’s State Council 2017).

The plan addresses everything from building basic AI theory to partnerships with industry to fostering educational programs and building an AI-savvy society.

Recommendations

Recommendations to foster the U.S.’s AI advancement include focusing efforts on further proliferating Science, Technology, Engineering and Math (STEM)programs to develop the next generation of developers. This is similar to China’s AI development plan which calls to “accelerate the training and gathering of high-end AI talent.” This lofty goal creates sub-steps, one of which is to construct an AI academic discipline. While there are STEM programs in the U.S., according to the U.S. Department of Education, “The United States is falling behind internationally, ranking 29th in math and 22nd in science among industrialized nations.” To maintain the top position in AI, the U.S. must continue to develop and attract the top engineers and scientists. This requires both a deliberate plan for academic programs as well as funding and incentives to develop and maintain these programs across U.S. institutions. Perhaps most importantly, the United States needs to figure out a strategy to entice more top American students to invest their time and attention to this proposed new discipline. Chinese and Russian students easily outpace American students in this area, especially in terms of pure numbers.

Additionally, the U.S. must research and capitalize on the dual-use capabilities of AI. Leading companies such as Google and IBM have made enormous headway in the development of algorithms and machine-learning. The Department of Defense should levy these commercial advances to determine relevant defense applications. However, part of this partnership with industry must also consider the inherent national security risks that AI development can present, thus introducing a regulatory role for commercial AI development. Thus, the role of the U.S. government with AI industry cannot be merely as a consumer, but also as a regulatory agent. The dangerous risk, of course, is this effort to honor the principles of ethical and transparent development will not be mirrored in the competitor nations of Russia and China.

Due to the population of China and lax data protection laws, the U.S. has to develop innovative ways to overcome this challenge in terms of machine-learning and artificial intelligence. China’s large population creates a larger pool of people to develop as engineers as well as generates a massive volume of data to glean from its internet users. Part of this solution is investment. A White House report on AI indicated, “the entire U.S. government spent roughly $1.1 billion on unclassified AI research and development in 2015, while annual U.S. government spending on mathematics and computer science R&D is $3 billion.” If the U.S. government considers AI an instrument of national security, then it requires financial backing comparable to other fifth-generation weapon systems. Furthermore, innovative programs such as the DOD’s Project Maven must become a mainstay.

Project Maven, a pilot program implemented in April 2017, was mandated to produce algorithms to combat big data and provide machine-learning to eliminate the manual human burden of watching full-motion video feeds. The project was expected to provide algorithms to the battlefield by December of 2018 and required partnership with four unnamed startup companies. The U.S. must implement more programs like this that incite partnership with industry to develop or re-design current technology for military applications. To maintain its technological advantage far into the future the U.S. must facilitate expansive STEM programs, seek to capitalize on the dual-use of some AI technologies, provide fiscal support for AI research and development, and implement expansive, innovative partnership programs between industry and the defense sector. Unfortunately, at the moment, all of these aspects are being engaged and invested in only partially. Meanwhile, countries like Russia and China seem to be more successful in developing their own versions, unencumbered by ‘obstacles’ like democracy, the rule of law, and the unfettered free-market competition. The AI Race is upon us. And the future seems to be a wild one indeed.

References

Allen, Greg, and Taniel Chan. “Artificial Intelligence and National Security.” Publication. Belfer Center for Science and International Affairs, Harvard University. July 2017. Accessed April 9, 2018. https://www.belfercenter.org/sites/default/files/files/publication/AI%20NatSec%20-%20final.pdf

Allen, John R., and Amir Husain. “The Next Space Race is Artificial Intelligence.” Foreign Policy. November 03, 2017. Accessed April 09, 2018. http://foreignpolicy.com/2017/11/03/the-next-space-race-is-artificial-intelligence-and-america-is-losing-to-china/.

China. State Council. Council Notice on the Issuance of the Next Generation Artificial Intelligence Development Plan. July 20, 2017. Translated by RogierCreemers, Graham Webster, Paul, Paul Triolo and Elsa Kania.

Doubleday, Justin. 2017. “Project Maven’ Sending First FMV Algorithms to Warfighters in December.” Inside the Pentagon’s Inside the Army 29 (44). Accessed April 1, 2018.https://search-proquest-com.ezproxy2.apus.edu/docview/1960494552?accountid=8289.

Flournoy, Michèle A., and Robert P. Lyons. “Sustaining and Enhancing the US Military’s Technology Edge.” Strategic Studies Quarterly 10, no. 2 (2016): 3-13. Accessed April 12, 2018. http://www.jstor.org/stable/26271502.

Gams, Matjaz. 2017. “Editor-in-chief’s Introduction to the Special Issue on “Superintelligence”, AI and an Overview of IJCAI 2017.” Accessed April 14, 2018. Informatica 41 (4): 383-386.

Louth, John, and Trevor Taylor. 2016. “The US Third Offset Strategy.” RUSI Journal 161 (3): 66-71. DOI: 10.1080/03071847.2016.1193360.

Sadler, Brent D. 2016. “Fast Followers, Learning Machines, and the Third Offset Strategy.” JFQ: Joint Force Quarterly no. 83: 13-18. Accessed April 13, 2018. Academic Search Premier, EBSCOhost.

Scharre, Paul, and SSQ. “Highlighting Artificial Intelligence: An Interview with Paul Scharre Director, Technology and National Security Program Center for a New American Security Conducted 26 September 2017.” Strategic Studies Quarterly 11, no. 4 (2017): 15-22. Accessed April 10, 2018.http://www.jstor.org/stable/26271632.

“Science, Technology, Engineering and Math: Education for Global Leadership.” Science, Technology, Engineering and Math: Education for Global Leadership. U.S. Department of Education. Accessed April 15, 2018. https://www.ed.gov/stem.

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Global anxiety deepens over online data and privacy protection

MD Staff

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Internet users worldwide are becoming more worried about their privacy online and many question the protections offered by Internet and social media companies, a new United Nations survey has found.

This waning of confidence could imperil the spread of online shopping even as newcomers to the Internet may be especially vulnerable to abuses because they are unaware of the risks.

Trust is essential for the successful expansion and use of e-commerce platforms and mobile payment systems in developing nations,” said Fen Osler Hampson, Director of Global Security and Politics at Centre for International Governance Innovation (CIGI), a think tank that helped conduct the study.

The survey was carried out by CIGI and Ipsos, in collaboration with the UN Conference for Trade and Development (UNCTAD) and the Internet Society.

Users in large emerging economies expressed the most “trust” in Internet firms with nine in ten expressing such faith in China, India and Indonesia and more than eight in ten doing so in Pakistan and Mexico.

To the contrary, fewer than 60 percent of consumers in Japan and Tunisia expressed such “trust.”

Privacy concerns

The evidence of mounting privacy concerns coincides with sharper public scrutiny of the protection policies of major Internet firms – over concerns fuelled by the revelation that a political data firm gained access to millions of Facebook users’ personal data without their consent.

“The survey underlines the importance of adopting and adapting policies to cope with the evolving digital economy” said Shamika Sirimanne, the Director of Technology and Logistics Division at the UN agency, which deals with the economics of globalization.

“The challenge for policymakers is to deal holistically with a number of areas – from connectivity and payment solutions to skills and regulations,” she explained.

Is technology worth the cost? Yes and No

As e-commerce soars, there is also a general increase in the number of people using mobile payments and non-traditional means of paying for services, such as tapping one’s smart phone to board trains or scanning it to pay for a cup of coffee.

The use of smart phones to make cashless purchases is in fact far higher in many developing countries than it is in the United States and much of Europe, the study noted.

In addition, many people, especially in the developing world, expressed the view that new technology is “worth what it costs.”

At the same time, some users in developed countries expressed views to the contrary. Their main worry, the survey found, is that technology will result in the loss of employment.

The launch of the survey coincides with UNCTAD’s E-Commerce Week – the leading forum for Governments, private sector, development banks, academia and the civil society to discuss development opportunities and challenges before the evolving digital economy.

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Embracing Technology is Key for the Jobs of Tomorrow in Latin America and the Caribbean

MD Staff

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New technologies provide a pathway to poverty reduction and could usher in a wave of higher productivity and growth across Latin America and the Caribbean, according to a new World Bank report.

At a time of growing fears of a future where automation replaces employees, technological innovation could create more and better jobs in the coming years—for both for skilled and unskilled workers in the region, the report Jobs of Tomorrow: Technology, Productivity, and Prosperity in Latin America and the Caribbean finds.

“We should adopt and promote technology and innovation to boost economic growth, poverty reduction and increase opportunities for all, rather than creating barriers,” said Jorge Familiar, World Bank Vice-President for Latin America and Caribbean. “Better education and training will be key to ensure youth can take full advantage of the digital world and be prepared for the work of tomorrow.”

According to the report, Latin America and the Caribbean has lower rates of digital technology adoption than similar countries in the Organization for Economic Co-operation and Development (OECD), providing ample space to increase productivity. Barriers also often drive up the price of productivity-enhancing technology. For example, smartphones and tablets in some countries in the region are the most expensive in the world. Tariffs and taxes on technology may be holding back per capita GDP growth by more than 1 percentage point a year across the region.

“With more technology comes more productivity,” said report author Mark Dutz, World Bank Lead Economist of the Macroeconomics, Trade and Investment Global Practice. “Companies can lower variable costs, expand production, reach more markets, make more money and in the process create more and better jobs.”

Studies on Argentina, Brazil, Chile, Colombia and Mexico find that lower-skilled workers can, and often do, benefit from adopting digital technologies. In addition, technology can have a strong impact on worker mobility, making it easier for job seekers to find information about job opportunities. It works both ways, making for better employer-employee matches.

Online trading platforms also level the playing field between small and large firms seeking access to international markets. International transactions over the Internet disproportionately benefit smaller firms – the same firms that tend to hire relatively more lower-skilled workers.

The report recommends some key areas where policies can help harness the productive power of this digital revolution. They include:

  • Making technologies available to local firms at globally-competitive prices. In Colombia, for example, manufacturing firms who adopted the use of high speed internet saw a direct increase in demand for laborers and lower-skilled production workers as well as higher-skilled professional workers.
  • Ensuring that firms have incentives to invest in technology upgrading and exports rather than seeking protection from competition. Policies and institutions that encourage firms to compete lead them to invest in improving their product quality and lowering costs and prices rather than investing in obtaining government privileges. Firms can also benefit from adopting better management practices to increase production and distribution – an area with huge potential in the region.
  • Educating workers to prepare them for the jobs of tomorrow that will demand new, more sophisticated skills. In Brazil, for instance, more technology-intensive industries increasingly rely on employees to do more cognitive and analytical tasks in which communication and interpersonal skills are in particularly high demand.

Turning away from technology because of fears about technological change would be a costly mistake. New technologies can and should be embraced to support shared prosperity across Latin America and the Caribbean, the report concludes.

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