SCI COMMUN### Computer science The United States will establish a dozen centers to study artificial intelligence (AI) and quantum information science (QIS), the White House announced last week. The seven university-based AI centers will receive $20 million each over 5 years from the National Science Foundation or the Department of Agriculture and will use AI—algorithms that can learn to recognize patterns—to tackle problems in areas ranging from farming to particle physics. The five centers on QIS, located at the Department of Energy's national laboratories, will focus on topics such as developing quantum computers that could solve challenges that would overwhelm conventional computers. Each of these centers will receive $125 million over 5 years, as Congress called for in the 2018 National Quantum Initiative Act. ### Archaeology Tiny parasitic worms known as helminths cause malnutrition and developmental disorders in some 1.5 billion people around the world, mostly in developing countries. Scientists now report new evidence that better sanitation can alleviate this scourge. During the Middle Ages and for centuries after, worm infections were as prevalent among Europeans as they are today in people living in parts of sub-Saharan Africa, South America, and East Asia, the authors report in a paper published on 27 August in PLOS Neglected Tropical Disease . They based the conclusion on an analysis of 589 samples from skeletons in medieval cemeteries in the Czech Republic, Germany, and the United Kingdom. Because such worms were eradicated in Europe before effective antiparasite drugs were developed, the results reinforce the idea that improvements to water supplies, sanitation, and hygiene can dramatically reduce the disease burden they cause today. ### Disasters When it roared ashore last week in Louisiana, Hurricane Laura packed a double whammy, endangering public safety with its wind and water and slowing efforts to stem the COVID-19 pandemic. Its top wind speed at landfall, 241 kilometers per hour, was the fifth highest documented for any U.S. hurricane. Laura tied a record for the fastest intensifying storm in the Gulf of Mexico, with its wind increasing on 26 August by 105 kilometers per hour in just 24 hours; the causes of such rapid strengthening are little understood. The storm led to at least 19 deaths in Louisiana and Texas. It also threatened to accelerate the spread of COVID-19; testing centers were temporarily closed, and residents of southwest Louisiana, which bore the storm's brunt and had been recording some of the state's highest rates of positive test results, evacuated elsewhere. Seven hurricanes and tropical storms have hit the United States so far this year, one of the most active seasons on record. ### Agriculture The Dutch government last week decided to end mink farming to prevent the animals from becoming sources of the virus that causes COVID-19. More than 40 mink farms in the Netherlands—almost one in three—have had outbreaks of the virus since late April, triggering massive culls. A Dutch law adopted in 2012 banned mink farming by 2024 for ethical reasons, but now the remaining farms must close by March 2021. The government has set aside €182 million to indemnify farmers. Although farms implemented hygiene rules, scientists suspect infected people carried the virus into them. Denmark, Spain, and the United States have seen outbreaks at mink farms as well. ### Public health By testing dormitory wastewater for SARS-CoV-2, the virus that causes COVID-19, the University of Arizona may have stamped out a potential outbreak before it could spread. Several countries, U.S. municipalities, and some universities have been checking sewage for RNA from the virus, which can signal infections shortly before clinical cases and deaths are recorded. In Arizona, officials announced last week that wastewater from a student dormitory contained the viral RNA just days after students had moved into their rooms in August; all 311 residents and dorm workers had previously tested negative on a mandatory test for COVID-19. The university retested all of them and found two students who were asymptomatic but positive for the virus; they were then quarantined. ### Diagnostics The U.S. Food and Drug Administration last week issued an emergency use authorization to Abbott, a laboratory company, for a 15-minute test for the COVID-19 virus that could help expand the number of Americans regularly tested. The new diagnostic, called BinaxNOW, detects proteins, or antigens, that are unique to the virus with high accuracy and at a cost of only $5 each. Other coronavirus tests that identify genetic material unique to the virus typically cost $100, and laboratories often take days to provide results. The genetic tests and other, antigen-based ones require specialized lab equipment; Abbott's does not, although a health care professional must administer it. The company says it plans to produce 50 million tests in October. Last week, the Trump administration announced it would buy 150 million. The United States currently conducts about 700,000 tests for the virus per day. ### Policy The U.S. Centers for Disease Control and Prevention (CDC) drew criticism last week for revising its guidelines to state that people exposed to the virus that causes COVID-19 “do not necessarily need a test” if they lack symptoms and do not have medical conditions that make them vulnerable. Scientists and public health specialists slammed the 24 August revision, noting that people who do not feel sick can still spread the virus and that the United States continues to lead the world in COVID-19 cases and deaths. Trump administration officials have said too many people have been getting tested out of fear and tests should be reserved for those at highest risk, The New York Times reported. But CDC Director Robert Redfield appeared to muddy the message when he said on 26 August that testing “may be considered for all close contacts of confirmed or probable COVID-19 patients.” ### Infectious diseases The EcoHealth Alliance, a nonprofit whose highly scored grant to study bat coronaviruses that could jump to humans in China was summarily defunded after President Donald Trump targeted it, has received new funding worth $7.5 million over 5 years, the U.S. National Institutes of Health (NIH) announced last week. In April, Trump alleged without evidence that the COVID-19 virus escaped from the Wuhan Institute of Virology; the EcoHealth Alliance had collaborated with scientists there on the canceled grant. NIH ended it days later, drawing strong protests from scientists. The newly funded work will not revive the earlier project but instead will focus on risks of animal viruses jumping to humans in Southeast Asia, but not China. The EcoHealth Alliance is one of 11 groups NIH plans to fund with $82 million to study such risks. “It's a relief for us to know that NIH isn't going to blackball our organization because of political interference,” EcoHealth Alliance President Peter Daszak says. ### Funding China continued in 2019 its yearslong run of double-digit annual percentage increases in spending on R&D. But it has not yet reached its long-standing goal of increasing R&D expenditures to 2.5% of gross domestic product (GDP). Total public and private science and technology expenditures in 2019 rose 12.5% to 2.21 trillion Chinese yuan ($322 billion), the National Bureau of Statistics of China reported last week. Most (83%) went to development, while basic research received 6% and applied research 11%. Relative to other countries, China has been spending more on development and less on basic research. Its total R&D spending in 2019 amounted to 2.23% of GDP, still short of the United States's 2.83%. China was the world's second biggest spender on R&D behind the United States in 2018, the latest year for which a comparison is available, according to the Organisation for Economic Co-operation and Development. Analysts expect China to continue to close the gap. ### Astronomy Gravitational wave hunters have netted a big fish: the signal from a pair of black holes merging to produce one with a mass of about 142 Suns. That heft makes it the first confirmed intermediate-mass black hole, with a mass between those produced by collapsing stars and the giant black holes at the hearts of galaxies. Detected in May 2019 by the twin Laser Interferometer Gravitational-wave Observatory facilities in the United States and the Virgo detector in Italy, the merger is also the most distant seen, at 7 billion light-years away, as well as the most powerful, with the mass of eight Suns converted into energy. The masses of the individual black holes—85 and 66 solar masses—before they merged pose a puzzle, as theorists believe it impossible to make a black hole heavier than 65 Suns from the collapse of a single star. The discovery is reported this week in Physical Review Letters and The Astrophysical Journal Letters . ### Nonproliferation After a monthslong impasse, Iran has agreed to allow international inspectors access to two sites that were allegedly part of a clandestine nuclear weapons program. The move preserves, for now, what remains of a multination nuclear deal reached in 2015, from which the Trump administration has withdrawn. The inspections will take place at Abadeh, a testing range for high explosives in central Iran, and at an undisclosed site, which intelligence reports revealed might have contained undeclared nuclear materials and activities. Iran had rebuffed requests from the International Atomic Energy Agency to take samples at the sites; continued stonewalling could have prompted the agency to declare Iran out of compliance with its commitments. The United States maintains that Iran has violated the nuclear deal, and banking and other sanctions lifted after the 2015 accord must automatically resume. But members of the United Nations Security Council last week reiterated their disagreement with that interpretation, and the United States now plans to reimpose those sanctions unilaterally on 20 September. ### Environment The Trump administration on 31 August eased rules on toxic wastewater created by coal-burning power plants, which operators discharge into rivers and streams. The move changes a rule adopted in 2015 by former President Barack Obama's administration requiring plant operators to treat and recycle water used to store coal ash, which contains mercury and arsenic, by 2023. The Trump administration's version instead exempts plants set to close or switch to natural gas by 2028 and allows other plants to delay compliance until that year if they voluntarily adopt advanced biological treatment. The administration says its rule will save the industry money and retain coal-industry jobs while reducing total pollution by 1 million pounds annually, over and above the 1.4 million pound reduction anticipated under the Obama rule. But environmental groups rejected those assertions and predicted that power plants—now the largest contributors of industrial water pollution—will discharge even more. The critics add that the move will prop up coal power, which is responsible for emitting a significant share of global warming gases. ### Conservation A Norwegian wind farm has devised an inexpensive method that may prevent birds from being killed by turbines' rotating blades. By painting only one turbine blade black, the farm reduced bird collisions by more than 70%, say researchers who conducted the first field study of the approach. Fast-moving, monotone blades can be difficult for birds to see; in the United States alone, collisions with wind turbines kill 140,000 to 500,000 birds each year. But a single contrasting black blade makes this rotating obstacle easier for birds to identify and avoid, researchers report in the 27 August issue of Ecology and Evolution . The approach needs further validation, other researchers say. And they note that windmills still rank low on the list of threats to birds: Collisions with power wires and communication towers kill an estimated 32 million birds in the United States annually, for example, and cats are believed to kill 2.4 billion each year. Loss of habitat is another leading threat. ### Infectious diseases Togo is the first African country to have eliminated Human African trypanosomiasis (HAT), better known as sleeping sickness, as a public health problem. The World Health Organization (WHO) on 25 August certified the country as free of HAT, which is caused by two subspecies of the Trypanosoma brucei parasite and spread by tsetse flies. Occurring only in sub-Saharan Africa, HAT causes neurological damage and is fatal when left untreated. Surveillance and control programs have helped bring reported cases down sharply, from more than 25,000 in 2000 to 980 last year. WHO hopes the subspecies T. b. gambiense , which occurs in West and Central Africa and is responsible for more than 98% of cases, can be eliminated altogether by 2030. “I am sure [Togo's] efforts will inspire others,” Matshidiso Moeti, WHO regional director for Africa, said in a statement. 3.4 million —Square kilometers of sea floor changed by human activities, such as the construction of ports, communication cables, oil rigs, and wind farms, as of 2018, representing an estimated 1.5% of all coastal areas. ### Why it matters The modified area equals that of cities on land, and its marine ecosystems may have sustained damage ( Nature Sustainability ).

Redistricting—the constitutionally mandated, decennial redrawing of electoral district boundaries—can distort representative democracy. An adept map drawer can elicit a wide range of election outcomes just by regrouping voters (see the figure). When there are thousands of precincts, the number of possible partitions is astronomical, giving rise to enormous potential manipulation. Recent technological advances have enabled new computational redistricting algorithms, deployable on supercomputers, that can explore trillions of possible electoral maps without human intervention. This leaves us to wonder if Supreme Court Justice Elena Kagan was prescient when she lamented, “(t)he 2010 redistricting cycle produced some of the worst partisan gerrymanders on record. The technology will only get better, so the 2020 cycle will only get worse” ( Gill v. Whitford ). Given the irresistible urge of biased politicians to use computers to draw gerrymanders and the capability of computers to autonomously produce maps, perhaps we should just let the machines take over. The North Carolina Senate recently moved in this direction when it used a state lottery machine to choose from among 1000 computer-drawn maps. However, improving the process and, more importantly, the outcomes results not from developing technology but from our ability to understand its potential and to manage its (mis)use. It has taken many years to develop the computing hardware, derive the theoretical basis, and implement the algorithms that automate map creation (both generating enormous numbers of maps and uniformly sampling them) ([ 1 ][1]–[ 4 ][2]). Yet these innovations have been “easy” compared with the very difficult problem of ensuring fair political representation for a richly diverse society. Redistricting is a complex sociopolitical issue for which the role of science and the advances in computing are nonobvious. Accordingly, we must not allow a fascination with technological methods to obscure a fundamental truth: The most important decisions in devising an electoral map are grounded in philosophical or political judgments about which the technology is irrelevant. It is nonsensical to completely transform a debate over philosophical values into a mathematical exercise. As technology advances, computers are able to digest progressively larger quantities of data per time unit. Yet more computation is not equivalent to more fairness. More computation fuels an increased capacity for identifying patterns within data. But more computation has no relationship with the moral and ethical standards of an evolving and developing society. Neither computation nor even an equitable process guarantees a fair outcome. The way forward is for people to work collaboratively with machines to produce results not otherwise possible. To do this, we must capitalize on the strengths and minimize the weaknesses of both artificial intelligence (AI) and human intelligence. Ensuring representational fairness requires metacognition that integrates creative and benevolent compromises. Humans have the advantage over machines in metacognition. Machines have the advantage in producing large numbers of rote computations. Although machines produce information, humans must infuse values to make judgments about how this information should be used ([ 5 ][3]). ![Figure][4] Time to regroup Markedly different outcomes can emerge when six Republicans and six Democrats in these 12 geographic units are grouped into four districts. A 50-50 party split can be turned into a 3:1 advantage for either party. When redistricting a state with thousands of precincts, the potential for political manipulation is enormous. GRAPHIC: X. LIU/ SCIENCE Accordingly, machines can be tasked with the menial aspects of cognition—the meticulous exploration of the astronomical number of ways in which a state can be partitioned. This helps us classify and understand the range of possibilities and the interplay of competing interests. Machines enhance and inform intelligent decision-making by helping us navigate the unfathomably large and complex informational landscape. Left to their own devices, humans have shown themselves to be unable to resist the temptation to chart biased paths through that terrain. The ideal redistricting process begins with humans articulating the initial criteria for the construction of a fair electoral map (e.g., population equality, compactness measures, constraints on breaking political subdivisions, and representation thresholds). Here, the concerns of many different communities of interest should be solicited and considered. Note that this starting point already requires critical human interaction and considerable deliberation. Determining what data to use, and how, is not automatable (e.g., citizen voting age versus voting age population, relevant past elections, and how to forecast future vote choices). Partisan measures (e.g., mean-median difference, competitiveness, likely seat outcome, and efficiency gap) as well as vote prediction models, which are often contentious in court, should be transparently specified. Once we have settled on the inputs to the algorithm, the computational analysis produces a large sample of redistricting plans that satisfy these principles. Trade-offs usually arise (e.g., adhering to compactness rules might require splitting jagged cities). Humans must make value-laden judgments about these trade-offs, often through contentious debate. The process would then iterate. After some contemplation, we may decide, perhaps, on two, not three, majority-minority districts so that a particular town is kept together. These refined goals could then be specified for another computational analysis round with further deliberation to follow. Sometimes a Pareto improvement principle applies, with the algorithm assigned to ascertain whether, for example, city splits or minority representation can be maintained or improved even as one raises the overall level of compliance with other factors such as compactness. In such a process, computers assist by clarifying the feasibility of various trade-offs, but they do not supplant the human value judgments that are necessary for adjusting these plans to make them “humanly rational.” Neglecting the essential human role is to substitute machine irrationality for human bias. Automation in redistricting is not a substitute for human intelligence and effort; its role is to augment human capabilities by regulating nefarious intent with increased transparency, and by bolstering productivity by efficiently parsing and synthesizing data to improve the informational basis for human decision-making. Redistricting automation does not replace human labor; it improves it. The critical goal for AI in governance is to design successful processes for human-machine collaboration. This process must inhibit the ill effects from sole reliance on humans as well as overreliance on machines. Human-machine collaboration is key, and transparency is essential. The most promising institutional route in the near term for adopting this human-machine line-drawing process is through independent redistricting commissions (IRCs) that replace politicians with a balanced set of partisan citizen commissioners. IRCs are a relatively new concept and exist in only some states. They have varied designs. In eight states, a commission has primary responsibility for drawing the congressional plan. In six, they are only advisory to the legislature. In two states, they have no role unless the legislature fails to enact a plan. IRCs also vary in the number of commissioners, partisan affiliation, how the pool of applicants is created, and who selects the final members. The lack of a blueprint for an IRC allows each to set its own rules, paving the way for new approaches. Although no best practices have yet emerged for these new institutions, we can glean some lessons from past efforts about how to integrate technology into a partisan balanced deliberation process. For example, Mexico's process integrated algorithms but struggled with transparency, and the North Carolina Senate relied heavily on a randomness component. Both offer lessons and help us refine our understanding of how to keep bias from creeping into the process. Once these structural decisions are made, we must still contend with the fact that devising electoral maps is an intricate process, and IRCs generally lack the expertise that politicians and their staffs have cultivated from decades of experience. In addition, as the bitter partisanship of the 2011 Arizona citizen commission demonstrated, without a method to assess the fairness of proposals, IRCs can easily deadlock or devolve into lengthy litigation battles ([ 6 ][5]). New technological tools can aid IRCs in fulfilling their mandate by compensating for this experience deficiency as well as providing a way to benchmark fairness conceptualizations. To maintain public confidence in their processes, IRCs would need to specify the criteria that guide the computational algorithm and implement the iterative process in a transparent manner. Open deliberation is crucial. For instance, once the range of maps is known to produce, say, a seven-to-eight likely split in Democrat-to-Republican seats 35% of the time, an eight-to-seven likely Democrat-to-Republican split 40% of the time, and something outside these two choices 25% of the time, how does an IRC choose between these partisan splits? Do they favor a split that produces more compact districts? How do they weigh the interests of racial minorities versus partisan considerations? Regardless of what technology may be developed, in many states, the majority party of the state legislature assumes the primary role in creating a redistricting plan—and with rare exceptions, enjoys wide latitude in constructing district lines. There is neither a requirement nor an incentive for these self-interested actors to consent to a new process or to relinquish any of their constitutionally granted control over redistricting. All the same, technological innovation can still have benefits by ameliorating informational imbalance. Consider redistricting Ohio's 16 congressional seats. A computational analysis might reveal that, given some set of prearranged criteria (e.g., equal population across districts, compact shapes, a minority district, and keeping particular communities of interest together), the number of Republican congressional seats usually ends up being 9 out of 16, and almost never more than 11. Although the politicians could still then introduce a map with 12 Republican seats, they would now have to weigh the potential public backlash from presenting electoral districts that are believed, a priori, to be overtly and excessively partisan. In this way, the information that is made more broadly known through technological innovation induces a new pressure point on the system whereby reform might occur. Although politicians might not welcome the changes that technology brings, they cannot prevent the ushering in of a new informational era. States are constitutionally granted the right to enact maps as they wish, but their processes in the emerging digital age are more easily monitored and assessed. Whereas before, politicians exploited an information advantage, scientific advances can decrease this disparity and subject the process to increased scrutiny. Although science has the potential to loosen the grip that partisanship has held over the redistricting process, we must ensure that the science behind redistricting does not, itself, become partisanship's latest victim. Scientific research is never easy, but it is especially vulnerable in redistricting where the technical details are intricate and the outcomes are overtly political. We must be wary of consecrating research aimed at promoting a particular outcome or believing that a scientist's credentials absolve partisan tendencies. In redistricting, it may seem obvious to some that the majority party has abused its power, but validating research that supports that conclusion because of a bias toward such a preconceived outcome would not improve societal governance. Instead, use of faulty scientific tests as a basis for invalidating electoral maps allows bad actors to later overturn good maps with the same faulty tests, ultimately destroying our ability to legally distinguish good from bad. Validating maps using partisan preferences under the guise of science is more dangerous than partisanship itself. The courts must also contend with the inconvenient fact that although their judgments may rely on scientific research, scientific progress is necessarily and excruciatingly slow. This highlights a fundamental incompatibility between the precedential nature of the law and the unrelenting need for high-quality science to take time to ponder, digest, and deliberate. Because of the precedential nature of legal decision-making, enshrining underdeveloped ideas has harmful path-dependent effects. Hence, peer review by the relevant scientific community, although far from perfect, is clearly necessary. For redistricting, technical scientific communities as well as the social scientific and legal communities are all relevant and central, with none taking over the role of another. The relationship of technology with the goals of democracy must not be underappreciated—or overappreciated. Technological progress can never be stopped, but we must carefully manage its impact so that it leads to improved societal outcomes. The indispensable ingredient for success will be how humans design and oversee the processes we use for managing technological innovation. 1. [↵][6]1. W. K. T. Cho, 2. Y. Y. Liu , arXiv:2007.11461 (22 July 2020). 2. 1. W. K. T. Cho, 2. Y. Y. Liu , “A massively parallel evolutionary Markov chain Monte Carlo algorithm for sampling complicated multimodal state spaces,” paper presented at SC18: The International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, TX, 11 to 16 November 2018. 3. 1. Y. Y. Liu, 2. W. K. T. Cho, 3. S. Wang , Swarm Evol. Comput. 30, 78 (2016). [OpenUrl][7] 4. [↵][8]1. Y. Y. Liu, 2. W. K. T. Cho , Appl. Soft Comput. 90, 106129 (2020). [OpenUrl][9] 5. [↵][10]Conceptualizing “fairness” for a diverse society with overlapping and incongruous interests is complex ([ 7 ][11]). Although we primarily discuss algorithmic advances that enable automated drawing and uniform sampling of maps, other measurement issues remain. Stephanopoulos and McGhee ([ 8 ][12]) suggest that the efficiency gap, their measure of “wasted votes,” should be the same across parties. Chikina et al. ([ 9 ][13]) submit that a map should not be “carefully crafted” (i.e., producing different outcomes than geographically similar maps). Fifield et al. ([ 10 ][14]) and Herschlag et al. ([ 11 ][15]) present local ensemble sampling approaches to identify gerrymanders. Each of these is but one point in a massive evolving discussion. Along these lines, Warrington ([ 12 ][16]) explores various partisan gerrymandering measures. Saxon ([ 13 ][17]) examines the impact of various compactness measures; Cho and Rubinstein-Salzedo ([ 14 ][18]) discuss the concept of “carefully crafted” maps; and Cho and Liu ([ 15 ][19]) highlight difficulties involved in uniformly sampling maps. 6. [↵][20]1. B. E. Cain , Yale Law J. 121, 1808 (2012). 7. [↵][21]1. B. J. Gaines , in Rethinking Redistricting: A Discussion About the Future of Legislative Mapping in Illinois (Institute of Government and Public Affairs, University of Illinois, Urbana-Champaign, Chicago, and Springfield, 2011), pp. 6–10. 8. [↵][22]1. N. O. Stephanopoulos, 2. E. M. McGhee , Univ. Chic. Law Rev. 82, 831 (2015). [OpenUrl][23][Abstract/FREE Full Text][24] 9. [↵][25]1. M. Chikina, 2. A. Frieze, 3. W. Pegden , Proc. Natl. Acad. Sci. U.S.A. 114, 2860 (2017). 10. [↵][26]1. B. Fifield, 2. M. Higgins, 3. K. Imai, 4. A. Tarr , J. Comput. Graph. Stat. 10.1080/10618600.2020.1739532 (2020). 11. [↵][27]1. G. Herschlag et al ., Stat. Public Policy 10.1080/2330443X.2020.1796400 (2020). 12. [↵][28]1. G. S. Warrington , Elect. Law J. 18, 262 (2019). [OpenUrl][29] 13. [↵][30]1. J. Saxon , Elect. Law J. 28, 372 (2020). [OpenUrl][31] 14. [↵][32]1. W. K. T. Cho, 2. S. Rubinstein-Salzedo , Stat. Public Policy 6, 44 (2019). [OpenUrl][33] 15. [↵][34]1. W. K. T. Cho, 2. Y. Y. Liu , Physica A 506, 170 (2018). Acknowledgments: W.K.T.C. has been an expert witness for A. Philip Randolph Institute v. Householder, Agre et al. v. Wolf et al. , and The League of Women Voters of Pennsylvania et al. v. The Commonwealth of Pennsylvania et al. 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A US technology company is 3D-printing futuristic holiday homes starting from $100,000 (£75,000) that fit in a back garden. Mighty Buildings, based in Oakland, California, says it can manufacture a 350 square-foot studio unit in less than 24 hours, providing owners a peaceful hideaway or a holiday cabin to accommodate guests. The firm is offering a variety of units on its website, ranging from a dinky studio to a luxury family home, which are printed with liquid synthetic stone that hardens almost instantly. The buildings are constructed at the company's facilities, transported to the customer's property on a truck and placed in a back garden with a massive crane. Units could also be leased out by property owners to help tackle the housing crisis, or big companies could also buy them to house employees while they're looking for something more long-term.

Artificial intelligence (AI) has already been identified as a crucial technology front, as nations and companies jockey to gain the edge in developing AI-driven applications. The potential impact of AI cannot be understated in today's business, with AI being considered a force multiplier because of its capacity to amplify company resources and to maximize output. Technology powerhouses are well aware of the ability of AI to transform businesses in a variety of ways, which explains why so much money is being poured into AI startups. Spend on AI systems is expected to top US$77.6 billion in 2022, according to one IDC report, while another commissioned by Microsoft illustrated that AI will almost double the rate of innovation and workforce productivity in the Asia Pacific (APAC) region in the next three years. With plenty of innovation being driven by AI, protecting these artificial intelligence inventions becomes crucial as well. And not just by organizations – the US government has pledged to boost spending on AI next year by as much as US$1.5 billion, with US' chief technology officer, Michael Kratsios, implicitly stating that the Trump administration had taken "unprecedented action to prioritize American leadership in AI […]" as the technology is increasingly seen as having strategic implications for the innovation leaders.

Machine learning creates room for continuous business model innovation. One recent summer, Charles Weinstein, CEO of New York City-based accounting firm EisnerAmper, had an epiphany: machine learning could either destroy his business or remake it. A 35-year veteran of the industry, Weinstein sensed that the practice of accounting--issuing financial statements three months after the quarter closes--while still necessary, was losing relevance in the real-time, data-driven economy. So he organized a three-day partner meeting to consider how machine learning capabilities in particular might remake the traditional accounting firm for the digital era, enabling it to help its clients look into the future rather than simply reporting on the past. Weinstein invited a partner in charge of global innovation at a Big Four accounting firm (not a direct competitor) to talk about the moves his firm was making.

This article is a transcript of a presentation I gave to the Rotary eClub of Silicon Valley about Clearview AI, a facial recognition company which the New York Times said "might end privacy as we know it." My presentation was based on an article earlier this year in Medium's OneZero. Thanks to the whole Rotary eClub team for the opportunity to present. This is the Rotary eClub of Silicon Valley. Every week, we are trying to bring you cool and interesting material that will make you go, "Hmm. That's interesting," and hopefully will inspire you to act in some way, whether that's act in service, or perhaps even act in self defense. Because we are going to learn some really interesting stuff over the coming minutes, and that is a function of having as our speaker today, Thomas Smith. He goes by Tom when we were just speaking, so I'll refer to him as Tom. And Tom wrote an article recently that I found in OneZero, I think, via Medium. And I finished reading that article and thought, "Holy poop." So, so as a result of that, I actually reached out to him to say, "Could you speak to our Rotary eClub of Silicon Valley? And he was gracious enough to write back.

The "AI in Government - Forecasts from 2020 to 2025" report has been added to ResearchAndMarkets.com's offering. The Artificial Intelligence (AI) in government market was valued at US$4.904 billion in 2019. In recent years, government in different countries are taking a keen interest in artificial intelligence (AI) technology. They are increasingly investing in artificial intelligence (AI), spending budget, and time on pilot programs for various AI applications while discussing with people in the filed on the future implications of this technology for various public projects. The growing volume of big data is the major factor that is increasing the adoption of artificial intelligence (AI) technology across the government sector as it reduces the cost of storing and processing that data.

In a groundbreaking ruling, CMS has granted Viz.ai the first New Technology Add-on Payment (NTAP) for artificial intelligence software. NTAP, part of the CMS Inpatient Prospective Payment System (IPPS), was set up to support the adoption of cutting-edge technologies that have demonstrated substantial clinical improvement and ensure early availability to Medicare patients. In the US, stroke is the number one cause of long term disability, but is a treatable condition if identified early enough. Viz.ai has been recognized by Forbes, Fast Company, and AuntMinnie as one of the leading AI healthcare companies in the US. The company provides software that improves clinical and financial outcomes1,2 by streamlining acute care, leading to shorter time to treatment, improved patient outcomes, reduced length of stay, and increased number of procedures.

From car insurance quotes to which posts you see on social media, our online lives are guided by invisible, inscrutable algorithms. They help private companies and governments make decisions -- or automate them altogether -- using massive amounts of data. But despite how crucial they are to everyday life, most people don't understand how algorithms use their data to make decisions, which means serious problems can go undetected. The New Zealand government has a plan to address this problem with what officials are calling the world's first algorithm charter: a set of rules and principles for government agencies to follow when implementing algorithms that allow people to peek under the hood. By leading the way with responsible algorithm oversight, New Zealand hopes to set a model for other countries by demonstrating the value of transparency about how algorithms affect daily life.

Equifax's chief executive resigned from the company following its 2017 data breach, as did Target's chief executive in 2014. At Sony, the co-chair of the business stepped down from that role after embarrassing emails were publicly leaked by hackers, but she stayed on at the company. To be sure, the burden of responsibility for successful hacks still falls largely on chief information and security officers, rather than chief executives. But experts say the issue of cybersecurity is now front-and-center for the seniormost corporate ranks. "Almost every CEO we talk to, the words that come out of their mouth are, 'I lose sleep and our board loses sleep every night due to the fact that we could be compromised'," said Michael Piacente, co-founder and managing partner at Hitch Partners, a recruiting firm focused on cybersecurity professionals.