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Written by Suzanne Smalley May 25, 2022 | CYBERSCOOP

The U.S. militarys top expert on artificial intelligence (AI) said Wednesday that the Pentagon must up its game to ensure American supremacy in a future era where artificial intelligence will determine success on the battlefield.

China aims to dominate the world in the AI space by 2030, the Pentagons Joint Artificial Intelligence Director Lt. Gen. Michael Groen told an Atlantic Council-convened audience gathered for a discussion of AI in national security. Groen said that AI will be a $16 trillion industry by 2030, and will raise GDP significantly for both China and the U.S.

Groen said DOD must reinvent itself to meet the challenge, arguing that the Pentagon will need to do more to bring the branches together and act as a doer instead of a coordinating body. Citing Amazon founder Jeff Bezoss 2002 directive that all Amazon components must work with one organization-wide data set, Groen said that in the same way the Pentagon must lead its various components to be on more unified footing.

Its time for the Department of Defense to have a similar focus on using data to solve problems, to think about their problems through a data lens overcoming the cultural obstacles to actually become a competitive enterprise that can outfight any opponent and has the same level of productivity and efficiency that we desire for our taxpayers, Groen said. Clearly, the competition is around us.

Its time for the Department of Defense to have a similar focus on using data to solve problems, to think about their problems through a data lens overcoming the cultural obstacles to actually become a competitive enterprise that can outfight any opponent.

Acknowledging the difficulties inherent to adaptation for an agency bogged down by bureaucracy, Groen said he is focused on improving DODs efficiency as it seeks to take on the Chinese AI machine.

Implementation in the department, of course, is always a challenge as new technology meets legacy processes, legacy organizations and legacy technology, Groen said. Implementation, of course, is the key to successful transformation and implementation is extraordinarily challenging as artificial intelligence and related technologies cross cut not just service lines, but almost every procedural line or process line across the department.

Groen said China is now executing its 14th five-year plan to meet its goal for AI supremacy by 2030 while the U.S. is now building its 14th AI-based program objective memorandum (POM), which refers to how DOD allots future funding to meet its strategic objectives. Suggesting that the U.S. and China are locked in a neck at neck battle for AI dominance, Groen said, those dates, maybe uncomfortably, maybe comfortably, overlap to quite a degree.

Groens remarks were made at an event at which the Atlantic Councils Scowcroft Center for Strategy and Security unveiled a new report focused on artificial intelligence in national security and defense. The report warns that without intentional, coordinated, and immediate action, the United States risks falling behind competitors in the ability to harness game-winning technologies that will dominate the kinetic and non-kinetic battlefield of the future.

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Head of DOD artificial intelligence command warns Pentagon must improve to beat China on AI - CyberScoop

As artificial intelligence (AI) becomes increasingly embeddedinto products, services, and business decisions, state and locallawmakers have been considering and passing a range of lawsaddressing AI. These vary from laws that promote AI to moreregulatory approaches that impose obligations on AI in specificareas. In a development that parallels the evolution of privacylaws, states and localities have moved ahead with initiatives ontheir own. However, unlike in privacy, where a set of legislativeapproaches has been debated for years, approaches to dealing withAI have been far more varied and scattershot. This kind of apatchwork approach, if it continues, may create issues withmanaging regulatory compliance for many uses of AI acrossjurisdictions.

States and Localities Are Beginning to Move Forward with aPiecemeal Approach to AI

In 2021, five jurisdictions Alabama, Colorado, Illinois,Mississippi, and New York City enacted legislationspecifically directed at the use of AI. Their approaches varied,from creating bodies to study the impact of AI to regulating theuse of AI in contexts where governments have been concerned aboutincreased risk of harm to individuals.

Some of these laws have focused on promoting AI. For instance,Alabama's law establishes a council to review and advise theGovernor, the legislature, and other interested parties on the useand development of advanced technology and AI in the state. TheMississippi law implements a mandatory K-12 curriculum thatincludes instruction in AI.

Conversely, some laws are more regulatory and skeptical of AI.For example, Illinois has adopted two AI laws onethatdevelopsa task force to study the impactof emerging technologies, including AI, on the future of work andanother thatmandatesnotice, consent, and reportingobligations for employers that use AI in hiring. Under existingIllinois law, an employer that asks applicants to record videointerviews and uses an AI analysis must: (1) notify the applicantthat AI may be used to analyze the applicant's video interviewand consider the applicant's fitness for the position; (2)provide each applicant with information explaining how the AI worksand what general types of characteristics the AI uses to evaluateapplicants; and (3) obtain consent from the applicant. The law alsolimits the sharing of the videos and extends to applicants a rightto delete the videos. A 2021 amendment imposes reportingrequirements on an employer that relies solely upon an AI analysisof a video interview to determine whether an applicant will beselected for an in-person interview. The state Department ofCommerce and Economic Opportunity is required to annually analyzecertain demographic data reported and report to the Governor andGeneral Assembly whether the data discloses a racial bias in theuse of AI.

Colorado's law takes a sectoral approach,prohibitinginsurers from using anyinformation sources as well as any algorithms or predictive modelsin a way that produces unfair discrimination. Unfair discriminationincludes "the use of one or more external consumer data andinformation sources, as well as algorithms or predictive modelsusing external consumer data and information sources, that have acorrelation to race, color, national or ethnic origin, religion,sex, sexual orientation, disability, gender identity, or genderexpression, and that use results in a disproportionately negativeoutcome for such classification or classifications, which negativeoutcome exceeds the reasonable correlation to the underlyinginsurance practice, including losses and costs forunderwriting." This law comes in addition to Colorado'scomprehensive privacy law, theColorado Privacy Act, set to go into effect onJuly 1, 2023, which provides consumers with a right to opt out ofthe processing of their personal data for purposes of targetedadvertising, the sale of personal data, or automated profiling infurtherance of decisions that produce legal or similarlysignificant effects.

In late 2021, New York City notablyenacteda specific algorithmicaccountability law, becoming the first jurisdiction in the UnitedStates to require algorithms used by employers in hiring orpromotion to be audited for bias. New York City's law bars AIhiring systems that do not pass annual audits checking for race- orgender-based discrimination. The bill would require the developersof such AI tools to disclose the job qualifications andcharacteristics that will be used by the tool and would provideemployment candidates the option of choosing an alternative processfor employers to review their application. The law imposes fines onemployers or employment agencies of up to $1,500 per violation.

California's Privacy Regulations May Also TargetAI

California's California Privacy Protection Agency (CPPA), the new agency charged with rulemakingand enforcement authority over the California Privacy Rights Act(CPRA), is expected to issue regulations governing AI by 2023. Thestatute specifically addresses a consumer's right to understandand opt out of automating decision-making technologies such as AIand machine learning. In particular, the agency is charged with"[i]ssuing regulations governing access and opt-out rightswith respect to businesses' use of automated decisionmakingtechnology, including profiling and requiring businesses'response to access requests to include meaningful information aboutthe logic involved in those decisionmaking processes, as well as adescription of the likely outcome of the process with respect tothe consumer."

In September 2021, the CPPAreleasedan Invitation for PreliminaryComments on Proposed Rulemaking (Invitation) and accepted commentsthrough November 8, 2021. The Invitation to comment issued by theCPPA asked four questions regarding interpretation of theagency's automated decision-making rulemaking authority:

While the statute calls for final rules to be adopted by July2022, at a February 17 CPPA board meeting, Executive DirectorAshkan Soltani announced that draft regulations will be delayed. Aswe've previouslydiscussed, this effort in California toregulate certain automated decision-making processes may open thedoor to greater regulation of AI and should be watchedclosely.

Even as the federal governmentlooks more closelyat AI, some states andlocalities appear to be poised to jump ahead. Indeed, many otherstates continue to debate AI proposals in 2022. Companiesdeveloping and deploying AI should continue to monitor this area asthe regulatory landscape develops.

2022 Wiley Rein LLP

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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States And Localities Begin To Focus On Use Of Artificial Intelligence - New Technology - United States - Mondaq

Do you know what Artificial Intelligence is? This is a growing industry with great opportunities and a perfect place for investments. AI has appeared on the market as a working solution to make the life of people in every industry easier. Due to the massive investment plan in the sector, there are tons of teaching practices to master on the topic. You can find a lot of experts in the field who can teach you to become the leading AI specialist in the field.

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There are various sectors where AI can contribute successfully. It helps with process optimization and eases the work in general. When better effectiveness and results are needed, Artificial Intelligence comes to the fore. Hence, if you are interested in the topic and would like to be a part of the global tech sector, you need to start with thorough learning.

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Read: TeamViewer brings Artificial Intelligence to the Shopfloor

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Artificial Intelligence in Today's World: What's the Tendency? - TechnoSports

Ameco Research Analysts says that the global market for artificial intelligence (AI) in aviation will reach a market size of more than US$ 6,900 Mn by 2028 rising at a CAGR of around 47% during the predicted years

Airports around the world took the brunt of the travel prohibitions and limitations imposed by the COVID-19 outbreak in a short period of time. Operations have been severely affected or fully suspended since international travel has been restricted to repatriation planes and cargo, and most airport halls are almost empty. Machine learning (ML), deep learning (DL), and other artificial intelligence (AI) approaches are beginning to influence the industry and have become fundamental methodologies in many research initiatives and new industrial advances. Machine learning becomes easier with access to vast volumes of data, allowing us to address previously inconceivable issues. The use of artificial intelligence (AI) in aviation can help with capacity, forecasting, air traffic management (ATM), delay management, the environment, connectivity, and safety.

The growing adoption of big data inArtificial Intelligence (AI) in Aviation Marketgrowth

Quick reactions to present and future market demands, better planning and tactically aligned decision making, and a clear understanding and monitoring of all important performance drivers significant to the airline industry are the ultimate benefits of big data analytics. When these advantages are correctly exploited, they contribute to lower operating costs, market-leading competitiveness, better customer service, higher profit margins, and more shareholder value.

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While a variety of variables have contributed to the expansion of AI in travel, one of the most important has been a shift in customer expectations. Because of the experiences provided by huge tech companies like Google, Amazon, Apple, and Facebook, travelers are increasingly demanding seamless and personalized experiences.

By leveraging artificial intelligence through virtual assistant technology that reads weather forecasts on demand, switches radio channels, and delivers situational information on demand, airline pilots can save time and increase efficiency. AI-based virtual assistants can manage repeated chores thanks to their capabilities. Additionally, Garmin offers AI audio panels that can be beneficial to pilots.

Artificial intelligence can also help to reduce overbooking. Based on past flyer information and historical passenger data, as well as changes in weather trends on a certain route, AI might be used to anticipate if a specific passenger will not show up or will transfer to another aircraft. The AI would then offer ground employees the most up-to-date passenger information. This technology could make it easier to remove passengers from planes that have already taken off.

Global Artificial Intelligence (AI) in Aviation Market Classification

Artificial intelligence (AI) in aviation market is divided into four categories: offering, technology, application, and regions. The offering segment can be split into hardware, software, and services. Based on offering, the software segment generated the largest revenue in 2020 while the services are likely to attain the fastest growth rate during the forecast period 2021 2028. Machine learning, context awareness computing, natural language processing, and computer vision are the categorizations of technology segments. The machine learning application acquired the most market share in 2020, whereas the natural language processing segment is expected to grow with a significant growth rate. Computer vision, a technique that utilizes cameras and machine learning algorithms to monitor complicated ground servicing activities, detect safety hazards in real-time, or sound alerts when a service takes longer than intended, is one of the emerging AI applications at airports. Gatwick Airport in London was one of the first major airports to use computer vision to speed up aircraft turnaround times and improve ground personnel safety. Based on application, the market is divided into virtual assistants, smart maintenance, manufacturing, training, surveillance, flight operations, and dynamic pricing. Among applications, the virtual assistant segment dominated the market with maximum share and is also likely to exhibit the quickest growth in the coming years.

Regional Stance

North America, Asia-Pacific, Latin America, Europe, and the Middle East & Africa (MEA) are the regional categorization of the global artificial intelligence (AI) in aviation market. North America generated the largest revenue in 2020 due to the early adoption of technologies and the presence of key players in the region. Meanwhile, the Asia-Pacific region is expected to witness the fastest growth rate in the coming years. China and Japan are the two largest contributors to AIs growth in the APAC aviation sector. The deployment of machine learning and natural language processing (NLP) technology for virtual assistance and training applications in the aviation sector is boosting AIs growth in this region. These countries have a high demand for AI technology to improve the efficiency of their aviation sectors.

Major Players

The key companies offered in the report include Airbus SE, Boeing, Garmin Ltd., Amazon, IBM Corporation, Intel Corporation, Lockheed Martin, Micron Technology, General Electric, MiSmart Maintenanceoft, Neurala, Inc. NVIDIA corporation, MINDTITAN, TAV Technologies, Samsung Electronics, Thales Group, and Xilinx.

FEW SIGNIFICANT POINTS FROM TABLE OF CONTENT:

Global Artificial Intelligence (AI) in Aviation Market Research Report 2021-2028

CHAPTER 1. Industry Overview of Artificial Intelligence (AI) in Aviation MarketCHAPTER 2. Research ApproachCHAPTER 3. Market Dynamics And Competition AnalysisCHAPTER 4. Manufacturing Plant AnalysisCHAPTER 5. Artificial Intelligence (AI) in Aviation Market By OfferingCHAPTER 6. Artificial Intelligence (AI) in Aviation Market By TechnologyCHAPTER 7. Artificial Intelligence (AI) in Aviation Market By ApplicationCHAPTER 8. North America Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 9. Europe Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 10. Asia Pacific Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 11. Latin America Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 12. Middle East & Africa Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 13. Player Analysis Of Artificial Intelligence (AI) in Aviation MarketCHAPTER 14. Company Profile

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Artificial Intelligence (AI) in Aviation Market Sales and Revenue Report 2021 2030 The Daily Vale - The Daily Vale

Old Timer may be the oldest known humpback, first sighted Lynn Canal, Southeast Alaska 1972. Also sighted as PWF-NP1117 and HIHWNMS-2017-2-25WWG01A01 (Photo by Jim Nahmens, courtesy of Happy Whale)

Its a special moment, watching a gigantic humpback going for a deep dive. The whales back arches and the tail swings up, disappearing below the surface like the pointed toes of an Olympic diver.

The black-and-white patterns on the underside of a whales tail fins, or flukes, are unique. Now a citizen science program called Happy Whale uses artificial intelligence to quickly identify humpbacks from those patterns.

Through photographs shared by whale watchers, Happy Whale has recorded thousands of whales that travel to and from Alaska.

Like facial recognition, we can tell who it is, said Ted Cheeseman, an expedition scientist who has studied whales all over the world, including in Antarctica. He co-founded Happy Whaleas a way to track humpbacks, a species thats known to travel thousands of miles.

Its helping to answer a lot of questions about their individual behavior.

Who does the whale hang out with? Does the whale have a calf? Cheeseman said. What is the larger story here such that we can build family relationships and so on, tell more of the story of the individual. To me, thats a huge part of this.

The difference between this photo ID program and others in the past is the manpower needed. Happy Whale uses an automated computer program to ID the photos instead of people doing it by hand. Just one full-time and two part-time employees run the database and confirm the results.

The program started in 2015 but took years to test and fine tune. Now, whale watchers can share their fluke photos and locations to the online database, which has identified 68,000 humpbacks worldwide.

The program started with 18,000 whale photos that had been previously identified by hand. Cheeseman says Happy Whale is more efficient.

Somebody gives me a dataset of a thousand photos, it used to be that that would be an hour per photo, Cheeseman said. The actual matching time is now insignificant. If someone gives me a thousand photos I can tell them the next day that, Oh, 700 of them are these known whales and these 300, those are probably new.'

The program has documented about 30,000 humpbacks in the North Pacific, which Cheeseman expects is about 70% of the population.

Participants are rewarded for their work. They usually get an initial response within a few days to a week and get notices when their whale is spotted again.

Dennis Rogers, a long-time whale watching guide in Petersburg, has uploaded over 5,500 photos to the program.

Its very interesting just to see the migrations, Rogers said. Some of these whales go to Hawaii for the winter, and theyre re-sighted there, which we get a notification when that re-sighting happens. Some of our whales go to Mexico. Its real interesting, some of our whales go to Mexico one year and to Hawaii the next year.

Rogers encourages his clients to send in their photos as well. He says other tracking systems, including satellite tags, can fall off whales within days.

This is purely un-invasive and gives a great amount of information over time. Some of our whales, weve been tracking close to 40 years, Rogers said.

The program has found some unusual migrations in Alaskas individual whales, said Scott Roberge, a board member for Petersburgs Marine Mammal Center.

Theyve followed one from Alaska to Hawaii to Japan back to Alaska, Roberge said. Made the loop of the North Pacific.

Roberge also contributes photographs and enjoys getting the feedback.

Its incredible to get that information and to get the email that says, Oh, the whale that you took a picture of last summer was just found in Hawaii, and it just had a baby, he said.

Cheeseman believes that over 95% of humpbacks in Southeast Alaska are in the database already. But the program is expanding. Cheeseman hopes to automate dorsal fin recognition within the year, which would allow them to identify and track orcas and other species a lot faster.

Cheeseman gave a presentation in Petersburg on May 18 at the Wright Auditorium.

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Citizen science program uses photos and artificial intelligence to track thousands of humpback whales - KTOO