YUMA PROVING GROUND, Ariz. After weeks of work in the oppressive Arizona desert heat, the U.S. Army carried out a series of live fire engagements Sept. 23 at Yuma Proving Ground to show how artificial intelligence systems can work together to automatically detect threats, deliver targeting data and recommend weapons responses at blazing speeds.

Set in the year 2035, the engagements were the culmination of Project Convergence 2020, the first in a series of annual demonstrations utilizing next generation AI, network and software capabilities to show how the Army wants to fight in the future.

The Army was able to use a chain of artificial intelligence, software platforms and autonomous systems to take sensor data from all domains, transform it into targeting information, and select the best weapon system to respond to any given threat in just seconds.

Army officials claimed that these AI and autonomous capabilities have shorted the sensor to shooter timeline the time it takes from when sensor data is collected to when a weapon system is ordered to engaged from 20 minutes to 20 seconds, depending on the quality of the network and the number of hops between where its collected and its destination.

We use artificial intelligence and machine learning in several ways out here, Brigadier General Ross Coffman, director of the Army Futures Commands Next Generation Combat Vehicle Cross-Functional Team, told visiting media.

We used artificial intelligence to autonomously conduct ground reconnaissance, employ sensors and then passed that information back. We used artificial intelligence and aided target recognition and machine learning to train algorithms on identification of various types of enemy forces. So, it was prevalent throughout the last six weeks.

Promethean Fire

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The first exercise featured is informative of how the Army stacked together AI capabilities to automate the sensor to shooter pipeline. In that example, the Army used space-based sensors operating in low Earth orbit to take images of the battleground. Those images were downlinked to a TITAN ground station surrogate located at Joint Base Lewis McCord in Washington, where they were processed and fused by a new system called Prometheus.

Currently under development, Prometheus is an AI system that takes the sensor data ingested by TITAN, fuses it, and identifies targets. The Army received its first Prometheus capability in 2019, although its targeting accuracy is still improving, according to one Army official at Project Convergence. In some engagements, operators were able to send in a drone to confirm potential threats identified by Prometheus.

From there, the targeting data was delivered to a Tactical Assault Kit a software program that gives operators an overhead view of the battlefield populated with both blue and red forces. As new threats are identified by Prometheus or other systems, that data is automatically entered into the program to show users their location. Specific images and live feeds can be pulled up in the environment as needed.

All of that takes place in just seconds.

Once the Army has its target, it needs to determine the best response. Enter the real star of the show: the FIRES Synchronization to Optimize Responses in Multi-Domain Operations, or FIRESTORM.

What is FIRESTORM? Simply put its a computer brain that recommends the best shooter, updates the common operating picture with the current enemy situation, and friendly situation, admissions the effectors that we want to eradicate the enemy on the battlefield, said Coffman.

Army leaders were effusive in praising FIRESTORM throughout Project Convergence. The AI system works within the Tactical Assault Kit. Once new threats are entered into the program, FIRESTORM processes the terrain, available weapons, proximity, number of other threats and more to determine what the best firing system to respond to that given threat. Operators can assess and follow through with the systems recommendations with just a few clicks of the mouse, sending orders to soldiers or weapons systems within seconds of identifying a threat.

Just as important, FIRESTORM provides critical target deconfliction, ensuring that multiple weapons systems arent redundantly firing on the same threat. Right now, that sort of deconfliction would have to take place over a phone call between operators. FIRESTORM speeds up that process and eliminates any potential misunderstandings.

In that first engagement, FIRESTORM recommended the use of an Extended-Range Cannon Artillery. Operators approved the algorithms choice, and promptly the cannon fired a projectile at the target located 40 kilometers away. The process from identifying the target to sending those orders happened faster than it took the projectile to reach the target.

Perhaps most surprising is how quickly FIRESTORM was integrated into Project Convergence.

This computer program has been worked on in New Jersey for a couple years. Its not a program of record. This is something that they brought to my attention in July of last year, but it needed a little bit of work. So we put effort, we put scientists and we put some money against it, said Coffman. The way we used it is as enemy targets were identified on the battlefield FIRESTORM quickly paired those targets with the best shooter in position to put effects on it. This is happening faster than any human could execute. It is absolutely an amazing technology.

Dead Center

Prometheus and FIRESTORM werent the only AI capabilities on display at Project Convergence.

In other scenarios, a MQ-1C Gray Eagle drone was able to identify and target a threat using the on-board Dead Center payload. With Dead Center, the Gray Eagle was able to process the sensor data it was collecting, identifying a threat on its own without having to send the raw data back to a command post for processing and target identification. The drone was also equipped with the Maven Smart System and Algorithmic Inference Platform, a product created by Project Maven, a major Department of Defense effort to use AI for processing full motion video.

According to one Army officer, the capabilities of the Maven Smart System and Dead Center overlap, but placing both on the modified Gray Eagle at Project Convergence helped them to see how they compared.

With all of the AI engagements, the Army ensured there was a human in the loop to provide oversight of the algorithms' recommendations. When asked how the Army was implementing the Department of Defenses principles of ethical AI use adopted earlier this year, Coffman pointed to the human barrier between AI systems and lethal decisions.

So obviously the technology exists, to remove the human right the technology exists, but the United States Army, an ethical based organization thats not going to remove a human from the loop to make decisions of life or death on the battlefield, right? We understand that, explained Coffman. The artificial intelligence identified geo-located enemy targets. A human then said, Yes, we want to shoot at that target.

Originally posted here:
Inside the Army's futuristic test of its battlefield artificial intelligence in the desert - C4ISRNet

The increasing reliance on AI systems also poses potential risks.

Underuse of AI is considered as a major threat: missed opportunities for the EU could mean poor implementation of major programmes, such as the EU Green Deal, losing competitive advantage towards other parts of the world, economic stagnation and poorer possibilities for people. Underuse could derive from public and business' mistrust in AI, poor infrastructure, lack of initiative, low investments, or, since AI's machine learning is dependent on data, from fragmented digital markets.

Overuse can also be problematic: investing in AI applications that prove not to be useful or applying AI to tasks for which it is not suited, for example using it to explain complex societal issues.

An important challenge is to determine who is responsible for damage caused by an AI-operated device or service: in an accident involving a self-driving car. Should the damage be covered by the owner, the car manufacturer or the programmer?

If the producer was absolutely free of accountability, there might be no incentive to provide good product or service and it could damage peoples trust in the technology; but regulations could also be too strict and stifle innovation.

The results that AI produces depend on how it is designed and what data it uses. Both design and data can be intentionally or unintentionally biased. For example, some important aspects of an issue might not be programmed into the algorithm or might be programmed to reflect and replicate structural biases. In adcition, the use of numbers to represent complex social reality could make the AI seem factual and precise when it isnt . This is sometimes referred to as mathwashing.

If not done properly, AI could lead to decisions influenced by data on ethnicity, sex, age when hiring or firing, offering loans, or even in criminal proceedings.

AI could severely affect the right to privacy and data protection. It can be for example used in face recognition equipment or for online tracking and profiling of individuals. In addition, AI enables merging pieces of information a person has given into new data, which can lead to results the person would not expect.

It can also present a threat to democracy; AI has already been blamed for creating online echo chambers based on a person's previous online behaviour, displaying only content a person would like, instead of creating an environment for pluralistic, equally accessible and inclusive public debate. It can even be used to create extremely realistic fake video, audio and images, known as deepfakes, which can present financial risks, harm reputation, and challenge decision making. All of this could lead to separation and polarisation in the public sphere and manipulate elections.

AI could also play a role in harming freedom of assembly and protest as it could track and profile individuals linked to certain beliefs or actions.

Use of AI in the workplace is expected to result in the elimination of a large number of jobs. Though AI is also expected to create and make better jobs, education and training will have a crucial role in preventing long-term unemployment and ensure a skilled workforce.

Read more:
Artificial intelligence: threats and opportunities | News - EU News

YUMA PROVING GROUND, Ariz. After weeks of work in the oppressive Arizona desert heat, the U.S. Army carried out a series of live fire engagements Sept. 23 at Yuma Proving Ground to show how artificial intelligence systems can work together to automatically detect threats, deliver targeting data and recommend weapons responses at blazing speeds.

Set in the year 2035, the engagements were the culmination of Project Convergence 2020, the first in a series of annual demonstrations utilizing next generation AI, network and software capabilities to show how the Army wants to fight in the future.

The Army was able to use a chain of artificial intelligence, software platforms and autonomous systems to take sensor data from all domains, transform it into targeting information, and select the best weapon system to respond to any given threat in just seconds.

Army officials claimed that these AI and autonomous capabilities have shorted the sensor to shooter timeline the time it takes from when sensor data is collected to when a weapon system is ordered to engaged from 20 minutes to 20 seconds, depending on the quality of the network and the number of hops between where its collected and its destination.

We use artificial intelligence and machine learning in several ways out here, Brigadier General Ross Coffman, director of the Army Futures Commands Next Generation Combat Vehicle Cross-Functional Team, told visiting media.

We used artificial intelligence to autonomously conduct ground reconnaissance, employ sensors and then passed that information back. We used artificial intelligence and aided target recognition and machine learning to train algorithms on identification of various types of enemy forces. So, it was prevalent throughout the last six weeks.

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The first exercise featured is informative of how the Army stacked together AI capabilities to automate the sensor to shooter pipeline. In that example, the Army used space-based sensors operating in low Earth orbit to take images of the battleground. Those images were downlinked to a TITAN ground station surrogate located at Joint Base Lewis McCord in Washington, where they were processed and fused by a new system called Prometheus.

Currently under development, Prometheus is an AI system that takes the sensor data ingested by TITAN, fuses it, and identifies targets. The Army received its first Prometheus capability in 2019, although its targeting accuracy is still improving, according to one Army official at Project Convergence. In some engagements, operators were able to send in a drone to confirm potential threats identified by Prometheus.

From there, the targeting data was delivered to a Tactical Assault Kit a software program that gives operators an overhead view of the battlefield populated with both blue and red forces. As new threats are identified by Prometheus or other systems, that data is automatically entered into the program to show users their location. Specific images and live feeds can be pulled up in the environment as needed.

All of that takes place in just seconds.

Once the Army has its target, it needs to determine the best response. Enter the real star of the show: the FIRES Synchronization to Optimize Responses in Multi-Domain Operations, or FIRESTORM.

What is FIRESTORM? Simply put its a computer brain that recommends the best shooter, updates the common operating picture with the current enemy situation, and friendly situation, admissions the effectors that we want to eradicate the enemy on the battlefield, said Coffman.

Army leaders were effusive in praising FIRESTORM throughout Project Convergence. The AI system works within the Tactical Assault Kit. Once new threats are entered into the program, FIRESTORM processes the terrain, available weapons, proximity, number of other threats and more to determine what the best firing system to respond to that given threat. Operators can assess and follow through with the systems recommendations with just a few clicks of the mouse, sending orders to soldiers or weapons systems within seconds of identifying a threat.

Just as important, FIRESTORM provides critical target deconfliction, ensuring that multiple weapons systems arent redundantly firing on the same threat. Right now, that sort of deconfliction would have to take place over a phone call between operators. FIRESTORM speeds up that process and eliminates any potential misunderstandings.

In that first engagement, FIRESTORM recommended the use of an Extended-Range Cannon Artillery. Operators approved the algorithms choice, and promptly the cannon fired a projectile at the target located 40 kilometers away. The process from identifying the target to sending those orders happened faster than it took the projectile to reach the target.

Perhaps most surprising is how quickly FIRESTORM was integrated into Project Convergence.

This computer program has been worked on in New Jersey for a couple years. Its not a program of record. This is something that they brought to my attention in July of last year, but it needed a little bit of work. So we put effort, we put scientists and we put some money against it, said Coffman. The way we used it is as enemy targets were identified on the battlefield FIRESTORM quickly paired those targets with the best shooter in position to put effects on it. This is happening faster than any human could execute. It is absolutely an amazing technology.

Prometheus and FIRESTORM werent the only AI capabilities on display at Project Convergence.

In other scenarios, a MQ-1C Gray Eagle drone was able to identify and target a threat using the on-board Dead Center payload. With Dead Center, the Gray Eagle was able to process the sensor data it was collecting, identifying a threat on its own without having to send the raw data back to a command post for processing and target identification. The drone was also equipped with the Maven Smart System and Algorithmic Inference Platform, a product created by Project Maven, a major Department of Defense effort to use AI for processing full motion video.

According to one Army officer, the capabilities of the Maven Smart System and Dead Center overlap, but placing both on the modified Gray Eagle at Project Convergence helped them to see how they compared.

With all of the AI engagements, the Army ensured there was a human in the loop to provide oversight of the algorithms' recommendations. When asked how the Army was implementing the Department of Defenses principles of ethical AI use adopted earlier this year, Coffman pointed to the human barrier between AI systems and lethal decisions.

So obviously the technology exists, to remove the human right the technology exists, but the United States Army, an ethical based organization thats not going to remove a human from the loop to make decisions of life or death on the battlefield, right? We understand that, explained Coffman. The artificial intelligence identified geo-located enemy targets. A human then said, Yes, we want to shoot at that target.

The rest is here:
The Army just conducted a massive test of its battlefield artificial intelligence in the desert - DefenseNews.com

For more than 100 years Nobel Prizes have been given out annually to recognize breakthrough achievements in chemistry, literature, medicine, peace, and physics. As these disciplines undoubtedly continue to impact society, newer fields like artificial intelligence (AI) and robotics have also begun to profoundly reshape the world.

In recognition of this, the worlds largest AI society the Association for the Advancement of Artificial Intelligence (AAAI) announced today the winner of their new Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity, a$1 million award given to honor individuals whose work in the field has had a transformative impact on society.

The recipient, Regina Barzilay, the Delta Electronics Professor of Electrical Engineering and Computer Science at MIT and a member of MITs Computer Science and Artificial Intelligence Laboratory (CSAIL), is being recognized for her work developing machine learning models to develop antibiotics and other drugs, and to detect and diagnose breast cancer at early stages.

In February, AAAI will officially present Barzilay with the award, which comes with an associated prize of $1 million provided by the online education company Squirrel AI.

Only world-renowned recognitions, such as the Association of Computing Machinerys A.M. Turing Award and the Nobel Prize, carry monetary rewards at the million-dollar level, says AAAI awards committee chair Yolanda Gil. This award aims to be unique in recognizing the positive impact of artificial intelligence for humanity.

Barzilay has conducted research on a range of topics in computer science, ranging from explainable machine learning to deciphering dead languages. Since surviving breast cancer in 2014, she has increasingly focused her efforts on health care. She created algorithms for early breast cancer diagnosis and risk assessment that have been tested at multiple hospitals around the globe, including in Sweden, Taiwan, and at Bostons Massachusetts General Hospital. She is now working with breast cancer organizations such as Institute Protea in Brazil to make her diagnostic tools available for underprivileged populations around the world. (She realized from doing her work that, if a system like hers had existed at the time, her doctors actually could have detected her cancer two or three years earlier.)

In parallel, she has been working on developing machine learning models for drug discovery: with collaborators shes created models for selecting molecule candidates for therapeutics that have been able to speed up drug development, and last year helped discover a new antibiotic called Halicin that was shown to be able to kill many species of disease-causing bacteria that are antibiotic-resistant, including Acinetobacter baumannii and clostridium difficile (c-diff).

Through my own life experience, I came to realize that we can create technology that can alleviate human suffering and change our understanding of diseases, says Barzilay, who is also a member of the Koch Institute for Integrative Cancer Research. I feel lucky to have found collaborators who share my passion and who have helped me realize this vision.

Barzilay also serves as a member of MITs Institute for Medical Engineering and Science, and as faculty co-lead for MITs Abdul Latif Jameel Clinic for Machine Learning in Health. One of the Jameel Clinics most recent efforts is AI Cures, a cross-institutional initiative focused on developing affordable Covid-19 antivirals.

Regina has made truly-changing breakthroughs in imaging breast cancer and predicting the medicinal activity of novel chemicals, says MIT professor of biology Phillip Sharp, a Nobel laureate who has served as director of both the McGovern Institute for Brain Research and the MIT Center for Cancer Research, predecessor to the Koch Institute. I am honored to have as a colleague someone who is such a pioneer in using deeply creative machine learning methods to transform the fields of health care and biological science.

Barzilay joined the MIT faculty in 2003 after earning her undergraduate at Ben-Gurion University of the Negev, Israel and her PhD at Columbia University. She is also the recipient of a MacArthur genius grant, the National Science Foundation Career Award, a Microsoft Faculty Fellowship, multiple best paper awards in her field, and MITs Jamieson Award for excellence in teaching.

"We believe AI advances will benefit a great many fields, from health care and education to smart cities and the environment," says Derek Li, founder and chairman of Squirrel AI. We believe that Dr. Barzilay and other future awardees will inspire the AI community to continue to contribute to and advance AIs impact on the world.

AAAIs Gil says the organization was very excited to partner with Squirrel AI for this new award to recognize the positive impacts of artificial intelligence to protect, enhance, and improve human life in meaningful ways. With more than 300 elected fellows and 6,000 members from 50 countries across the globe, AAAI is the worlds largest scientific society devoted to artificial intelligence. Its officers have included many AI pioneers, including Allen Newell and John McCarthy. AAAI confers several influential AI awards including the Feigenbaum Prize, the Newell Award (jointly with ACM), and the Engelmore Award.

Regina has been a trailblazer in the field of health care AI by asking the important questions about how we can use machine learning to treat and diagnose diseases, says Daniela Rus, director of CSAIL and the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science. She has been both a brilliant researcher and a devoted educator, and all of us at CSAIL are so inspired by her work and proud to have her as a colleague.

See the rest here:
Regina Barzilay wins $1M Association for the Advancement of Artificial Intelligence Squirrel AI award - MIT News

A tourist in Singapore taking in the iconic skyline with Marina Bay Sands and the Singapore Flyer in view.

IronHeart | Moment | Getty Images

Singapore is gradually reopening its borders again after months of coronavirus travel restrictions.

As the city-state looks to salvage its battered tourism industry which contributes around 4% to its economy it's hoped that artificial intelligence (AI) can help the sector bring back visitors safely.

Official datashowsmonthlyvisitor arrivals were down by 76% between January to July, compared to a year ago. Visitor arrivals in July alone were down more than 99% year-on-year.

Even though the Southeast Asian nation remains closed off to most foreigners, officials are now considering lifting restrictions for select groups of visitors.

Local start-ups like Vouch and Travelstop are betting on their AI-powered systems as the country navigates new security measures.

Launched in 2017, Vouch sells an AI-enabled digital concierge that's designed to answer guest inquiries, make bookings and take room service orders. The company says its chatbots used by hotels including Andaz Singapore and the Pan Pacificin Singapore can conduct health declarations, facilitate contactless ordering for dine-in services and manage crowd control.

The Vouch app being used on a mobile phone.

Handout from Vouch

"Interestingly, Covid-19 has actually helped our business significantly," Vouch co-founder Joseph Ling told CNBC.

The company had to initially modify its in-room dining ordering system to allow for takeaways and deliveries a feature that it gave to hotels for free during Singapore's partial lockdown.

"Thanks to this, we were able to build great relationships," Ling said. "When hotels began to plan for the future around June and July, we signed up many of them." He said Vouch is now growing rapidly with "15 percent of the total Singapore hotel room stock on board."

Other AI-backed firms also say they're optimistic about the long-term outlook.

Two-year-old Travelstop aims to simplify business travel with the help of its serverless SaaS platform, that's designed to speed up the booking process, automate expense reporting and provide cost-saving insights.

"For the past few months, even though corporate travel revenues have been down, we are seeing significant traction on our expense management platform as companies are now accelerating digitizing the workflows and processes to support the work from home culture," said Travelstop's co-founder Prashant Kirtane.

Ongoing border restrictions and lower consumer appetite for international flights have changed travel as an industry. The two entrepreneurs said they believe machine learning and AI will change travel as an experience.

"The business models of traditional corporate travel management companies have not evolved for decades," Kirtane stated. "Existing tools have not kept pace with the modern business traveler, and are generally not affordable by smaller and mid-sized businesses."

"Hotels used to feel more technologically advanced than our homes but as IoT (Internet of Things), AI and consumer tech companies take the lead, the tech gradient has reversed hotels now feel lower tech than our own homes," said Ling of Vouch. The Internet of Things is the idea of a network of devices thatare all connected to the internet and, conceptually at least, can work together.

Before the pandemic, AI and other forms of machine learning were just beginning to infiltrate the travel sector. Their biggest advantage is the ability to personalize experiences and streamline services based on customer data.

Singaporean start-up Fooyo, for example, creates customized itinerary planners that include real-time crowd monitoring for attractions and events. The app it created for the Chinese city of Chongqing also includes an AI audio guide, which gives visitors information based on their GPS location.

As the economy begins to recover from the pandemic,AI-backed systemscouldbecome especially useful.

For example, "with people being more cautious about being in long queues and waiting in crowded spaces, more AI processes would be beneficial to safe distancing," said James Walton, the transportation, hospitality and services sector leader at Deloitte Singapore. He cited the example of remote check-ins and check-outs in hotels.

Investors are paying attention to this rapidly growing sector. Travelstop raised $3 million in pre-Series A funding led by Silicon Valley venture capital firm Accel last year, on top of the $1.2 million it obtained in a 2019 seed round led by Singapore's SeedPlus.

Kirtane said the company aims to complete a new fundraising round in 2021. Vouch, meanwhile, has raised about $250,000 of angel investment to-date and will be seeking more funds as it looks to expand in Thailand and Malaysia.

And investments in new technology continue. In 2017, the country's tourism body and the Singapore Hotel Association launched a program to crowdsource technologies for hotels. Among the winners was a wireless system that automatically adjusts air-conditioning units for energy efficiency.

Officials announced an accelerator program for tourism-oriented tech start-ups late last year.

Technological innovation "can also strengthen investor perception, and thus encourage investments in the country," Walton said.

Singapore has long faced a severe labor crunch amid state-imposed foreign worker levies and quotas factors that have contributed to wage increases. For employers, "the use of tech and AI in areas such as hotel operations will go some way to alleviate this pressure," Walton said.

Ling of Vouch echoed those sentiments. Hiring is difficult for Singapore hotels since most locals don't want to work in hospitality, he explained. As a result, back-office staff are predominantly foreigners and due to quotas on foreign manpower, hotels often lack sufficient front-end personnel, Ling continued. With many establishments reducing staff count in the aftermath of Covid-19, labor issues are as critical as ever, he said.

Whilst AI can improve overall efficiency with less manpower, it can also lead to job losses an unwanted development at a time when people are already concerned about job security.

"Would this mean reducing foreign manpower numbers, and saving the jobs for Singaporeans? Does adopting [AI] replace the jobs, or would it enable more high-level jobs for Singaporeans?" Walton asked.

It remains to be seen, he said, how the government can balance that situation.

Correction: This story has been updated to accurately reflect the designation ofDeloitte's James Walton.

View post:
Singapore hopes artificial intelligence will help boost its tourism industry - CNBC

CHICAGO Artificial intelligence (AI) is another important component of modern loyalty, says Sastry Penumarthy, co-founder and vice president of strategy for Punchh, a loyalty firm based in San Mateo, Calif. Humans do not have the time or ability to sift through waves of data to know when and how to communicate and incentivize specific customers, and AI can make that process more seamless, and more personalized.

AI will basically let me predict the customers that will be of the highest value to me over the next three months, let me look at all the offers and let me find the right offer for each of these customers, says Penumarthy. He says Punchh is launching an AI-driven program like that with select customers over the next few months.

AI also helps companies identify and craft offers for customers who are visiting or purchasing less vs. the highest-value customers. It can identify the best time of day or day of the week to send an offer or a message to a loyalty member. So, for example, if you are in the habit of checking email at lunchtime, its useful to know that information, But I shouldnt ask you what you prefer; I learn from your behavior, he says.

Related: Loyalty, This Time Its Personal

But the most important reason to lean on AI, says Penumarthy, is its ability to connect consumer data collected through the loyalty program to other systems, such as marketing.

Penumarthy says Punchh is working on a way to extend and automate relationships between retailers, consumers and consumer packaged goods (CPG) brands.

Today, when retailers partner with CPG brands for loyalty promotions, it can take two to three months for the retailer to understand the effectiveness of the program and report back to the CPG company. With AI, both the CPG company and the retailer have a better idea of how much money and time to invest into the program.

Penumarthy says loyalty used to be much more conventional, but times have changed. People no longer use the same land line phone numbers they used to sign onto these programs years ago. Many customers no longer carry newspaper coupon clippings when shopping at the grocery store. I want the offers to be right there on the phone when Im placing the order. And they cant do that unless its personalized, says Penumarthy.

Jones of Caseys, which has partnered with Punchh, says understanding customer shopping patterns using data mining and AI is important, and that such tools will be a part of Caseys offer creation and targeting capabilities in the future.

More: 3 Loyalty Developments Driven by the Pandemic

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Artificial Intelligence in the C-Store - CSPDailyNews.com

U.S. Chief Technology Officer Michael Kratsios and Energy Secretary Dan Brouillette shed a little light on how the Energy Department and Trump administration are thinking about ethics, regulatory approaches, and broader societal implications as they push the rollout of artificial intelligence and other emerging technologies.

During a fireside chat in Pittsburgh Tuesday, Brouillette reflected on similar-but-as-serious considerations previously made when the agency was developing nuclear technologies many years ago. He noted that now, when focusing on ethics, his mind tends to hone in on negative aspects and bad results that could arise with tech adoption.

I haven't thought this through with great depth, but there seems to be some positive aspects of AI, too, on the ethics front that we need to explore, Brouillette told the chats moderator Carnegie Mellon University Vice President of Research Michael McQuade. And perhaps through that process we can speed the adoption of some of these technologies, he said, adding that hed like to give it all more thought.

Piggybacking off the point, Kratsios noted that while there's often a tendency to immediately start looking at the lenses of the negative, government officials should conduct a trade-off analysis in their tech-driven pursuits. President Trump signed an executive order on the American AI Initiative earlier in his term, he said, which called for a set of regulatory guidelines for agencies to lean on when implementing or overseeing the use of AI-powered technologies.

So, think about the [Food and Drug Administration] approving an AI medical diagnostic, or think about [the Federal Aviation Administration] approving a droneand what they should be considering in their regulatory approach, Kratsios explained.

A draft of the first set of regulatory guidelines was released earlier this year, which at the time were deemed by administration officials to make up a light-touch regulatory approach.

I think one of the core underpinnings of the way that the White House is directing agencies to think about this is to do that actual cost-benefit analysis, Kratsios said. The same cost-benefit analysis that is required by statute for any other regulation should also be done in the context of AI.

Noting that its something that is very hard to do, the CTO articulated that the guidelines would help provide clarity on how to see the benefits that these technologies can provide, weighed against some of the potential risks to ultimately create better regulatory solutions to providing the technology to the American public.

Brouillette also pointed out that other agencies such as the Homeland Security and Health and Human Services departments are already applying AI technologies to help find redundancies and duplications, and address other issues within their own regulatory processes. Now, the Energy Department aims to follow suit.

One of the questions that my predecessor asked me, Secretary Rick Perry, was are we going to apply this to ourselves? he said. And I think that's a very important common sense, fundamental first stepbut it's important that we do it as a regulatory agency.

The federal officials also touched on a range of other topics during the conversation, which was one part of several events Energy led in Pennsylvania this week.

Excerpt from:
Agencies Should Consider the Pros and Cons of Artificial Intelligence - Nextgov

Fitness routines have changed a lot during the pandemic. More people are opting to take their workout outside or choosing an indoor setting with minimal people.

Owner of The Exercise Coach in Brookfield Kristine Staral says their business model relies on smart technology that allows individuals to get the optimum workout in the shortest amount of time.

Our focus is on muscle quality over movement quantity- so its a safe, effective, and efficient workout and by that I mean our clients only need to commit to 2- 20 minute workouts a week. We do use smart technology along with certified coaches, said Staral.

Staral believes workout routines- married with smart technology- are the wave of the future.

We are definitely keeping up with the trend with todays smart technology. The equipment itself is built basically using artificial intelligence giving real time feedback thats unique to each individual.

To hear the entire conversation click on the link above.

Continued here:
Artificial Intelligence revamping exercise routines in the age of COVID-19 - WTMJ