Sooner or later, people will occupy outer space and look at the world from there. Ever since humans found that there exists a place beyond earth, the space race began. As the technology evolved, disruptive trends like artificial intelligence and machine learning are accelerating spacetech applications. While spacetech start-ups are ballooning like never before, giant technology companies are jumping into the spacetech market to score big. Today, the mother earth is undergoing a crucial time.

Artificial Intelligence might be a term for collecting concepts that allow computer systems to vaguely work like a brain. However, the use of numbers to represent complex social reality is flawed. AI might seem factual and precise when it isn't as the results that AI produces depend on how it is designed and what data it uses. At the moment in our everyday world, AI performs narrow tasks such as facial recognition, natural language processing, or internet searches but the pace of its progress is exponential and regardless of its benefits. The impact it is having is hard to ignore with more and more of the world's commerce becoming automated and trading going online.

Artificial intelligence has been credited with eliminating biases that undermine diversity, equity and inclusion in talent acquisition. With concern over racial injustice since George Floyd's death in police custody driving DEI to new heights, it's easy to miss the scourge of ageism. The Economic Policy Institute estimates that an inability of nearly three-fourths of workers age 65 and older to telecommute during the pandemic placed them at a higher risk for developing severe illnesses from COVID-19. In addition, the U.S. Bureau of Labor Statistics noted that long-term unemployment for working Americans 55 and older spiked to 26.4% from 14% last September vs. an increase to 18.2% from 11.3% outside that category. Experts note that so-called conversational AI can help ensure the safety of older talent as employees return to workplaces without ageism creeping into the equation post-pandemic.

American households are increasingly connected internally through the use of artificially intelligent appliances.1 But who regulates the safety of those dishwashers, microwaves, refrigerators, and vacuums powered by artificial intelligence (AI)? On March 2, 2021, at a virtual forum attended by stakeholders across the entire industry, the Consumer Product Safety Commission (CPSC) reminded us all that it has the last say on regulating AI and machine learning consumer product safety. The CPSC is an independent agency comprised of five commissioners who are nominated by the president and confirmed by the Senate to serve staggered seven-year terms. With the Biden administration's shift away from the deregulation agenda of the prior administration and three potential opportunities to staff the commission, consumer product manufacturers, distributors, and retailers should expect increased scrutiny and enforcement.2

This is higher than the global average of 47%, and quite understandable when read alongside the UK government's own report showing that nearly half (46%) of all businesses have been the victim of cybercrime in 2020 alone. Money laundering and terrorist financing are similarly huge industries: the National Crime Agency (NCA) considers it a'reasonable possibility' that the scale of money laundering in the UK is in the hundreds of billions of pounds. Given how pervasive digital crime is, the overall trajectory of the payments industry might seem counter-intuitive. More transactions are taking place online than ever before, meaning that finding fraudulent transactions is like finding a needle in a haystack that keeps growing. With millions of transactions being processed each day comes the need for regulation, so everyone at every step of the payment processing journey needs to ensure that they are compliant with evolving legislation.

High tech continues to make inroads in financial services, and now regulators want more insight -- and input -- into how technologies such as artificial intelligence (AI) can and are being used by enterprises. In a joint statement this week from the Federal Deposit Insurance Corporation, the Board of Governors of the Federal Reserve System, the Office of the Comptroller of the Currency, the Consumer Financial Protection Bureau and the National Credit Union Administration, those agencies are seeking information and commentary on how financial institutions (FIs) are being used in activities as far-flung as lending and risk management. As reported by PYMNTS earlier in the year, Mastercard Vice President, Global Head of Product for Artificial Intelligence (AI) Express and Credit Risk Amyn Dhala told Karen Webster in an interview that technology such as AI can make real-time risk management attainable. It can help banks reduce tens of millions of dollars in losses, which will get the attention of every financial services company on the planet. AI can also improve customers' interactions with their FIs, he said.

A metal head made of motor parts symbolizes artificial intelligence, or AI, at the Essen Motor Show for tuning and motorsports in Essen, Germany. The Comet petascale supercomputer at the San Diego Supercomputer Center at the University of California San Diego (UCSD) in San Diego used to develop artificial intelligence. MIT researchers are using the'Comet' MIT researchers are using the'Comet' supercomputer to develop an artificial intelligence. Harried supervisors will tell you managing a team is difficult in the best of times when face-to-face interaction happens daily and business is good. Providing constructive feedback to dispersed workers during a once-in-a-lifetime pandemic that has disrupted regular business can feel impossible.

The Joint Artificial Intelligence Center is out with a $241 million contract vehicle to help the Defense Department become ready for AI development by preparing data for the emerging technology. The Data Readiness for Artificial Intelligence Development services solicitation covers a five-year performance period and will result in multiple basic ordering agreements, according to the solicitation documents published Wednesday to beta.sam.gov. "The purpose of this Performance Work Statement (PWS) is to help the DoD and Government users prepare data for use in AI applications by providing an easily accessible path to access the cutting-edge commercial services needed to meet the complex technical challenges involved in preparing data for AI," the documents read. "Through access to AI data preparation tools, capabilities, and services, the DoD will be positioned to effectively prepare AI data to support the full range of AI activities across the DoD." The PWS indicates the services the Defense Department is looking for under this contract include curating, preparing, securing, and encrypting data for AI, securing, packaging and delivering AI tools, and making sure those tools can be integrated into cloud platforms.

In a September 2020 essay in Nature Energy, three scientists posed several "grand challenges" -- one of which was to find suitable materials for thermal energy storage devices that could be used in concert with solar energy systems. Fortuitously, Mingda Li -- the Norman C. Rasmussen Assistant Professor of Nuclear Science and Engineering at MIT, who heads the department's Quantum Matter Group -- was already thinking along similar lines. In fact, Li and nine collaborators (from MIT, Lawrence Berkeley National Laboratory, and Argonne National Laboratory) were developing a new methodology, involving a novel machine-learning approach, that would make it faster and easier to identify materials with favorable properties for thermal energy storage and other uses. The results of their investigation appear this month in a paper for Advanced Science. "This is a revolutionary approach that promises to accelerate the design of new functional materials," comments physicist Jaime Fernandez-Baca, a distinguished staff member at Oak Ridge National Laboratory.

To unleash the potential of AI safely, however, issues such as accuracy, human control, transparency, bias and privacy need to be addressed. So governments should be role-modelling the ethical use of AI, and educating their people on AI and how to be ready for the opportunities and challenges. One way countries could do this would be through setting up a body that is a visible focus for AI: a centre of excellence. Our project recommends this as a way to increase ethical AI use in a country and build public support for it across the economy and society. The centre could draw staff from industry, government, academia and civil society, using a multidisciplinary and collaborative approach to provide advice on AI and algorithm use for government operations. The centre would start to raise awareness on AI itself and encourage conversations about people's level of comfort with using it in different situations.