To mark Israel’s Memorial Day in 2021, the Israel Defense Forces musical ensembles collaborated with a company that specializes in synthetic videos, also known as “deepfake” technology, to bring photos from the 1948 Israeli-Arab war to life.
They produced a video in which young singers clad in period uniforms and carrying period weapons sang “Hareut,” an iconic song commemorating soldiers killed in combat. As they sing, the musicians stare at faded black-and-white photographs they hold. The young soldiers in the old pictures blink and smile back at them, thanks to artificial intelligence.
The result is uncanny. The past comes to life, Harry Potter style.
For the past few years, my colleagues and I at UMass Boston’s Applied Ethics Center have been studying how everyday engagement with AI challenges the way people think about themselves and politics. We’ve found that AI has the potential to weaken people’s capacity to make ordinary judgments. We’ve also found that it undermines the role of serendipity in their lives and can lead them to question what they know or believe about human rights.
Now AI is making it easier than ever to reanimate the past. Will that change how we understand history and, as a result, ourselves?
Low financial risk, high moral cost
The desire to bring the past back to life in vivid fashion is not new. Civil War or Revolutionary War reenactments are commonplace. In 2018, Peter Jackson painstakingly restored and colorized World War I footage to create “They Shall Not Grow Old,” a film that allowed 21st-century viewers to experience the Great War more immediately than ever before.
Live reenactments and carefully processed historical footage are expensive and time-consuming undertakings. Deepfake technology democratizes such efforts, offering a cheap and widely available tool for animating old photos or creating convincing fake videos from scratch.
But as with all new technologies, alongside the exciting possibilities are serious moral questions. And the questions get even trickier when these new tools are used to enhance understanding of the past and reanimate historical episodes.
Continue reading: https://thenextweb.com/news/slippery-slope-using-ai-and-deepfakes-to-reanimate-history

Nonfungible token-based projects like Loot and The N Project have helped spike interest in the Metaverse to an all-time high, raising hopes again that blockchain will finally break through to the masses. Will it, or is history doomed to repeat itself? The problem is that the very things that capture the imagination of the public are the very same things that ultimately degrade the performance of the underlying platforms and raise barriers to entry higher than ever. In this article, I’ll explore the fundamental issues responsible for creating this dynamic with the goal of helping address these issues once and for all.
The fundamental problem is that legacy blockchain technology — specifically Ethereum — introduces massive barriers to entry that hinder the ability of the Metaverse to onboard new users. These issues are then exacerbated by the failure to allow users of the network to statically price their network usage.
Apes and penguins are pricey
The fees required to use popular NFT marketplaces can be an insidious problem because projects often foist these costs onto the user with often-unrealistic expectations of their profit-making potential. A quick look through Etherscan reveals the mind-numbingly high value of transaction fees paid per project. Projects like Bored Ape Yacht Club and Pudgy Penguins have had their users pay 106.7 and 111.4 Ether (ETH), respectively, to interact with their smart contract. Combined, users of these two projects have had to pay nearly $1 million in transaction fees alone!
Continue reading: https://cointelegraph.com/news/how-blockchain-technology-might-bring-triple-a-games-to-metaverses

Even in the 21st century, where equality and diversity are usually encouraged in every industry, women have been left behind in cryptocurrency. Research by CNBC says that there are twice as many men (16%) investing in cryptocurrency as women (7%). The good news is that women-led initiatives are growing and providing mentorship and education to spike women’s interest in crypto and encourage inclusiveness.
Lavinia Osbourne runs a platform called Women in blockchain talks (WiBT), which was launched in 2019. The main objectives of WiBT are to amplify the voices of women in the space, promote diversity and inclusivity, provide education, and provide opportunities for event networking.
CryptoChicks is a non-profit educational organization based in Canada founded by Natalia Ameline and Elena Sinelnikova that offers mentorship in blockchain for women globally. The company also co-founded the Metis platform, which helps businesses transition to blockchain without coding.
Continue reading: https://www.investing.com/news/cryptocurrency-news/girl-power-in-crypto-new-projects-on-the-horizon-2670616

Talk to anyone within the fintech space right now and they’re almost guaranteed to tell you that regulation is one of the biggest challenges when it comes to innovating and operating in this industry.
Of course, this is for good reason, as regulation is vital for the safety and security of the consumers, the businesses and even the economy itself.
With regulation increasing in the sector in every global market, blockchain and its technologies has also seen an increase in regulatory scrutiny as the use of the technology is becoming more and more popular – not just in finance but across multiple industries. 
Russell Starr, CEO of DeFi Technologies said: “Whenever you have revolutions like blockchain that rock the very foundation of the status quo, you typically start without any regulations at all and then morph into standard regulation. Take the advent of internet technologies or biotech, for example, these technologies started out without regulations but later followed the traditional path of regulatory markets.
“Blockchain, on the other hand, is directed specifically towards destabilizing the status quo and traditional markets. Roughly 1% of the world has adopted or has exposure to crypto. If we are able to get to a world where people are comfortable with investing in blockchain and crypto — a world where everyone is able to realize its benefits, not just that 1 per cent — we need the global market to invest in them. And in order for Wall Street and Bay Street to gain a foothold to truly leverage the technology, the regulatory environment would need to catch up.
Continue reading: https://thefintechtimes.com/is-blockchain-technology-regulated/

America’s national security organizations have begun applying AI to more quickly and effectively produce intelligence assessments.
Speaking at the GovernmentCIO Media & Research AI: National Security virtual event, Director of the National Security Agency (NSA) Research Directorate Mark Segal discussed how these new capacities are assisting intelligence analysts in better processing and sorting large quantities of often complex and disparate information.
In outlining the NSA’s research priorities, Segal noted that both AI and machine-learning capacities already showed promise for better organizing the large pools of variable data their analysts sort through in producing regular assessments.
“One of the challenges that we have found AI to be particularly useful for is looking through the sheer amount of data that's created every day on this planet. Our analysts are looking at some of this data trying to understand it, and understand what its implications are for national security. The amount of data that we have to sort is going up pretty dramatically, but the number of people that we have who are actually looking at this data is pretty constant. So we're constantly looking for tools and technologies to help our analysts more effectively go through huge piles of data,” Segal said.
This application of AI to analysis has the potential to expedite the delivery of actionable intelligence to policymakers as well, who are able to more quickly and conclusively come to decisions based on a more effective sorting of available information.
“We analyze information and then provide that analysis to policymakers. For example, let’s say we're looking at a large pile of documents and trying to understand what the intentions of another country are by looking through that data quickly. We want to zoom in immediately on the most important parts of that data, and have our skilled analysts say, ‘We think this entity is doing a specific thing,’ and then leave that to the policymakers to determine how we might respond,” Segal said.
Segal cautioned that agency technologists need to start with a realistic understanding of AI and machine learning to make most effective use of these new capacities, and to see them in terms of how they can concretely refine internal processes and advance their organization’s key aims.
“One of the biggest risks about AI right now is that there's this huge amount of hype surrounding it … AI is a tool just like any other tool. And the way that you use a tool is to figure out where it would be effective, and where it would actually help solve a problem in our research organization. One of the things that we try to do is actually look at the technology in order to apply it to real problems and analyze the results in a scientifically rigorous manner,” Segal said.
Segal also cautioned agencies to avoid creating undue biases within their algorithms, as these built-in flaws would ultimately distort the resulting analysis in ways that are either ineffective or potentially dangerous if they go uncorrected.
Continue reading: https://governmentciomedia.com/ai-helping-refine-intelligence-analysis

STEM education can boost the role of women in AI and data science fields
Women are the key piece to the puzzle of realizing the highest maturity levels of digital enterprises, but unless we realize this, our progress in AI and technology will remain stagnant. To close the gender gap in science, technology, engineering, and math (STEM) and to accelerate advances in artificial intelligence and the sciences, we must encourage and support women on all levels, from the government to enterprise and establish equal employment opportunities for all.
Women make up a fraction of the artificial intelligence workforce, whether in the form of research and development or as employees at technology inclined firms. According to the World Economic Forum, “Non-homogeneous teams are more capable than homogenous teams of recognizing their biases and solving issues when interpreting data, testing solutions or making decisions.” In other words, diverse teams and especially those that emphasize women at their epicenter, are a necessary provision for enterprises to adopt, build, realize and accelerate enterprise AI maturity levels. At present, unfortunately, few enterprises understand the criticality of women to boost AI maturity levels.
STEM, data science, and AI fields experience a lack of female role models. Without female role models for girls to look up to, it becomes difficult for young women to envision future careers in science, technology, and engineering fields. A 2018 Microsoft survey shows that female STEM role models boost the interest of girls in STEM careers from 32 percent to 52 percent. Therefore, we must showcase the achievements of women in the sciences and engineering across the world to capture the attention of females everywhere.
One of the biggest pressures that females face in STEM careers is cutthroat competition amongst male counterparts and the toxic workplace culture that it creates. An HBR article found that three-fourths of female scientists support one another in their workplace to ease tensions. Moreover, women are likely to be demoted as inferior by men holding equivalent positions, whether those jobs are in engineering, data science, or AI. All of these factors contribute to females swiftly dismissing STEM jobs to avoid such disquieting workplace circumstances.
According to a survey conducted by BCG, when it comes to STEM, “Women place a higher premium on applied, impact-driven work than men do: 67% of women expressed a clear preference for such work, compared with 61% of men.” This finding highlights a significant fact: women are vastly more likely to pursue STEM roles that provide them with meaning, purpose and produce impactful results, but many women don’t perceive this purpose and impact in STEM jobs. Therefore, without a clear high impact-driven pathway insight, females tend to turn their heads on STEM, data science, and AI-related careers.
Continue reading: https://www.analyticsinsight.net/the-role-of-women-in-scalping-up-ai-and-data-science/

Advances in technology have fueled predictions the legal industry will have a very different look in the coming decades.
Much of the hype centers around artificial intelligence (AI) and how this can reduce legal costs and improve the quality of services for clients.
AI-based services aimed at smaller solicitors’ firms, allowing them to save time in the construction of legal documents such as wills, separation agreements and recovery claims, have been around for several years.
Large corporate law firms have also been investing in AI to, among other things, assist with high-volume document review.
But with these advances have come predictions of considerably less employment in the sector.
A report by an initiative of the Law Society of England and Wales earlier this year predicted a “savage reduction” in full-time jobs by 2050 and, in the more immediate term, the end of the partnership model, the deskilling of the legal profession as AI takes over and a dramatic drop in remuneration levels.
Continue reading: https://www.independent.ie/business/irelands-best-law-firms/the-jury-is-out-on-artificial-intelligence-41021065.html

If you are an investor who wants to support the advancement of women, there’s a category of investments for that: gender-lens funds.
These mutual funds and exchange-traded funds are part of the environmental, social and governance, or ESG, investing movement, and they specifically invest based on whether a company has women in leadership roles or is committed in some other way to women’s advancement and equity.
Morningstar MORN -0.17% Direct includes gender-lens funds in a group of 52 funds that seek to make a measurable impact on gender and diversity disparities. The research firm says $4.9 billion has flowed into this fund category this year through Sept. 30, up from $2.9 billion in the same period a year ago.
Parallelle Finance, a gender-lens advisory firm, says assets in the group of gender-lens stock funds it tracks rose 8% in the second quarter from the first quarter, helped by a combination of performance and net inflows. Assets in gender-lends bond funds grew 20% in the second quarter from the first, helped by new issuance, the firm says.
For investors who may be interested in this theme, here are some mutual funds and ETFs to consider.
Mutual funds
Pax Ellevate Global Women’s Leadership Fund (PXWEX). Pax Ellevate is one of the oldest offerings in the gender-lens category. The investor class of shares launched in 1993 and an institutional class launched in 2006. The fund tracks the Impax Global Women’s Leadership Index, which includes the highest-rated companies in the world for advancing women’s leadership, as determined by Impax Gender Analytics, an asset-management firm that creates investment criteria and indexes specifically focused on gender-lens investing. The fund includes approximately 400 companies that have made strides in areas including women in leadership roles, board positions and front-line positions. The fund also seeks to invest in companies that have gender parity in their pay policies and are transparent about gender diversity.
Continue reading: https://www.wsj.com/articles/gender-lens-funds-put-money-towards-women-leaders-11636056301

After being in the tech industry for more than a decade, software developer Charlene Hunter was shocked that she had never come across another Black female software developer.
That is until 2017 when, fed up of having no other Black women in her tech network, East Londoner Charlene founded Coding Black Females.
The non-profit network is a community and inspirational team that uplifts Black female developers, helps them find opportunities, and influences the tech industry to be more inclusive to people of colour.
"Initially it was to meet Black women in tech - I'm a software developer, and I hadn't met any other Black women who were software developers after 10 years in the industry," Charlene, 36, explained.
"I was inspired after I watched [2016 film] Hidden Figures, and it was the first time that I'd seen Black women as the focus in science and technology in the media.
"I thought there must be other people out there who are like me - I wanted to meet those people."
Coding Black Females, which Charlene runs alongside co-CTOs Tanya Powell and Efua Akumanyi and their team, has grown to be a large, global network which focuses on enabling Black women to find roles in the tech industry by working with organisations to connect members to roles that are available.
Continue reading: https://www.mylondon.news/news/east-london-news/meet-londoner-revolutionising-tech-industry-22078424

Women in technology can motivate more leadership roles with leading talents
Diversity has become a buzzword in the corporate landscape. To foster an all-encompassing workforce, it needs to start at the top. That is one reason why the upcoming years will start decorating the leadership roles with women. Female leaders are already making a remarkable stance in the tech circle and are devising a strategic future for the next generation of women to come. The ever-evolving, imaginative and inventive face of technology has welcomed an enormous number of women and in the future, it is anticipated to grow beyond the 50% mark.
Historically, women have been left out of the computing field. The worst case is that they have played a big role in building the computing industry from the ground up, but were often silenced and not given the recognition they deserved. Women’s voices and ideas can be found throughout the footprints of computers and technology, starting from introducing calculations in the early days to leading the global level artificial intelligence companies today. Fortunately, things have changed in the 21st century. Bringing dawn for women in technology, their leadership roles and talents are standing by them to showcase their presence.
Equality in technology starts from the root. Yes, education is the root here. For so many years, the pervasive myth that women are ‘right-brained and therefore more suited to creative or spontaneous pursuits has continued. But the tech sector is breaking the odds to recruit more women in leading roles where they can stand as an icon of power and creativity at the same time.
Every company is or is fast becoming a technology company. 
Continue reading: https://www.analyticsinsight.net/the-power-of-women-in-technology-is-evolving-to-house-more-leading-talents/

Discussions about a European regulation on artificial intelligence have burgeoned since the European Commission published its proposal in April. In the aftermath, we wrote about potential threats to labor and employment rights. The text, of course, is not definitive and it is possible the final version will significantly diverge—there is indeed room for improvement.
Amid calls from employers for a ‘laser-sharp’ definition, which would be prone to circumvention and unable to keep pace with technical developments, AI is described in the draft by reference to some of its functions: prediction, optimization, personalization and resource allocation. Due to the pandemic-induced digital acceleration, almost everyone is now familiar with the promises and perils of AI-enabled tools adopted to perform decisional tasks in a large variety of domains and, in particularly sensitive contexts, as working ecosystems.
The draft regulation mentions both ‘AI systems intended to be used for recruitment or selection of natural persons, notably for advertising vacancies, screening or filtering applications, evaluating candidates in the course of interviews or tests’ and ‘AI intended to be used for making decisions on promotion and termination of work-related contractual relationships, for task allocation and for monitoring and evaluating performance and behavior of persons in such relationships’. This largely encompasses the managerial functions entrusted to data-driven management models, often lumped together under the popular formula of ‘algorithmic bosses’.
Continue reading: https://socialeurope.eu/artificial-intelligence-and-workers-rights

These three layers of governance are critical in building ethical, effective AI.
The Ancient Greek playwrights knew how to tell a good story, but occasionally found themselves searching for a way to solve whatever conflict they had concocted. So they invented the “deus ex machina”—literally, god from the machine—in which an actor playing a god was brought on stage via a mechanical device to miraculously resolve the problem as only a god can do.
These days, artificial intelligence (AI) is becoming our version of the deus ex machina, promising to swoop in and solve our most pressing business problems. But, like the Greek gods, AI can be fickle and fallible.
AI has the potential to significantly improve the way we make decisions. It can also make recommendations that are unfair, harmful, and fundamentally wrong. There are a lot of ways bias can make it into our models, from poor data quality to spurious correlations.
Fortunately, though, by applying technological, ethical, and legal governance around the development and use of AI, we can significantly reduce the impact of bias in our models. 
Continue reading: https://www.forbes.com/sites/servicenow/2021/11/05/governing-the-future-of-ai/?sh=1fef47a52d2a

US Senator Bob Menendez, chair of the Senate Foreign Relations Committee, introduced a piece of legislation on Thursday that seeks to track and restrict the sale of American parts to Turkey's drone programme.
The legislation, an amendment to Congress' annual defence spending bill, would require the Biden administration to issue a report on Turkish drone exports beginning in 2018 and whether any of their drones contain American-made parts.
It would also require the administration to assess whether Turkey's drone exports are in violation of the US Arms Export Control Act or any other law. 
The Arms Export Control Act requires that any weapons the US gives to foreign governments, or in this case parts for a weapon, be only used for legitimate self-defence.
"Turkey's drone sales are dangerous, destabilizing and a threat to peace and human rights," Menendez said in a statement.
"The US should have no part of it, and this amendment is a recognition that we must prevent US parts from being included in these Turkish weapons."
Menendez also introduced another amendment that would end an exemption used to continue providing assistance to the government of Azerbaijan, which fought a conflict against Armenian forces in the disputed Nagorno-Karabakh region last year. 
"As the regime in Baku, with Turkey's support, continues choosing a path of violence instead of a peaceful, negotiated process between Armenia and Azerbaijan, it is long past time for this and all future administrations to halt this type of assistance and fully respect Section 907 of the FREEDOM Support Act," Menendez said.
During the conflict, Turkey shipped at least six armed attack drones to Baku while Turkish military staff helped shape Azerbaijan's strategy to capture the territory.
Continue reading: https://www.middleeasteye.net/news/top-us-senator-introduces-legislation-track-us-drone-parts-turkey

After reading about DJI’s latest drone, the Mavic 3, I was prompted to reflect on the speed technology in this area has progressed. DJI launched its Mavic series in September 2016, and it was already a highly competitive device, foldable, with a 12MPX camera capable of recording 4K videos at 24 fps, a flight time of 27 minutes (and all the features that have made flying a drone within anyone’s reach, with automatic stabilization and return to base (RTH) when the battery drops below a certain level), and a range of almost seven kilometers.
The new Mavic 3 comes with two Hasselblad cameras, one a 128º wide angle and the other a hybrid 28X telephoto lens, 5.1K video up to 50 fps or 4K video up to 120 fps, and capable of flying up to 46 minutes on a single charge and with a range of up to 15 kilometers, with an RTH function capable of even reading wind information or making decisions like flying over obstacles instead of around them to save energy.
I’m not going to be buying a DJI drone any time soon, nor is the company paying me for discussing it. However, the evolution of its technical specs is a great opportunity for me to talk about technological scenarios, because as its features perfectly prove, when we talk about technology, we have to make our plans around these kind of scenarios, where the key features of a device are perfectly capable of doubling in very few years, despite the fact that when they were launched we were already talking about highly optimized and very competitive devices.
In short, there is no comparison with the first drones that came on the market, which required considerable skill to prevent losing them if they ran out of battery over the course of their five-minute flights. In a very short time, we have moved to a completely different order of magnitude, which allows much more advanced uses, taking the use of drones to a very different dimension. Drones are now being used for a huge range of purposes.
At the same time, the legislative environment has adapted quickly: at the beginning of the development of a particular technology, we typically find problems, abuses or all kinds of situations that generate, sometimes, a certain level of concern in society. Over time, the law gradually adapts and adjusts, sometimes with steps backwards and forwards, with excessive restrictions giving way to a more pragmatic approach, with differences between different environments and countries, etc., until it becomes normalized. Thinking about a technology in the light of the limitations imposed by legislation at a given time, especially when it is in its infancy, tends to be of little practical use, and leads to incomplete analyses that undervalue it and reduce its scope.
Continue reading: https://medium.com/enrique-dans/drones-are-a-perfect-example-of-technological-progress-96e683752f31

Continue reading: https://tig.comptia.org/topic/new-topic/83hgnzq

While the use of sustainable agricultural practices has a multitude of environmental and production benefits, farmers face many barriers to adoption, including increased uncertainty of yields, a lack of expert technical assistance, a lack of the right equipment or technology, and most notably, the high cost of implementation.
The transition to sustainable farming requires conventional farmers to learn about new equipment, practices, and regulations. The largest source of farmer knowledge and technical assistance, county extension services, are geared toward conventional growers and woefully understaffed with organic and regenerative specialists needed for farmers to successfully transition.
Even with the right equipment, a farm cannot function without the workers to operate it. Tight profit margins in todays economic environment make hiring farm workers a challenge, and the ability to hire foreign workers through the federal government’s H2-A program requires hefty upfront expenses for transportation, attorneys, and housing that some farmers simply cannot afford.
For farmers weighing the risks and benefits of transitioning to more climate-smart agricultural practices, the high costs associated with transitioning remain one of the biggest obstacles. First, costs can be hard to predict, as climate-smart farming is not one-size-fits-all; the techniques are site-specific and determined by local weather and soil. Although certain financial incentive programs and overall economic benefits can help farmers enjoy increased profitability than conventional methods, the initial challenge of investing in necessary equipment can be daunting.
While the federal government has implemented some cost-sharing programs for farms seeking to grow more sustainably, the vast majority of federal farm support goes to the largest farms. In 2016, 60% of farm subsidies went to the richest 10% of farmers, many of whom work the land in ways that are fossil fuel intensive, exhaust soils, emit carbon, and contribute to the climate crisis.
Additionally, government support of regenerative practices is just beginning. Whereas conventional practices are often supported through tax breaks and subsidies, funding and research programs for soil improvement techniques do not yet enjoy the same level of support. In fact, a recent study found that the Environmental Quality Incentives Program (EQIP)—a federal program designed to deliver improved water quality and increase soil health—has strayed from its goals in recent years. In 2018, for example, soil boosting funding represented less than 1% of the United States Department of Agriculture’s total annual expenditures.
Yet, on-farm innovation, combined with new policy and advances in technology, offer the American agricultural sector with an array of hopeful solutions.
Continue reading: https://www.fastcompany.com/90693643/3-reasons-agriculture-is-poised-for-a-surge-of-sustainable-innovation

The amount of land and labor used on American farms has declined since the 1940s. Yet during the same period, agricultural output has nearly tripled, federal statistics show, because of one key factor: technology.
A main technological driver now boosting production in American agriculture is drones, which have enabled farms to increase crop yields while lowering pesticide use. The future of the agricultural industry, which recently celebrated National Farmers Day, lies in automating operations and adopting precision farming techniques, experts say.
Studies show that drones used in farming operations reduce costs. The average U.S. farmer using agricultural drones sees a return on investment of $12 per acre for corn, and $2 to $3 per acre for soybeans and wheat, according to research by the American Farm Bureau Federation.
“More farms are using drone technology and they are using better drone technology today than five years ago,” said Mohamed Mostafa, lead technical authority for mobile mapping for Applanix Corp., or Markham, Canada, which produces positioning and orientation systems for drones. “We have drones that fly longer times and have better cameras so you can see finer resolution on the ground.” Applanix is owned by software, hardware and services technology company Trimble.
Even small family-owned farms, which account for 90% of all U.S. farms, are integrating drones into their operations by contracting with service providers to deploy UAS for aerial mapping and crop spraying of fertilizer and pesticides.
With the average age of farmers in the United States rising to 57.5 years, drones are also helping to alleviate labor shortages and improving efficiency, said Louis Wasson, a senior extension associate at Mississippi State University and a drone instructor for USDA’s Wildlife Services.
“Drones save farmers a lot of time in not having to go out and spend time walking and looking at things,” Wasson said. “They can send the drone up and look at that precision spot. And you’re not spraying as much.”
Beyond Tractors and Crop Dusters
While farms have traditionally used tractors or crop dusters to spray crops with fertilizer and pesticides, that function is gradually being taken over by drones. Unmanned systems allow farmers to accurately pinpoint specific areas that need nutrients or protection from insects.
Tractors or crop dusters use a blanket approach to apply pesticides on entire fields, when only a portion of the crop may need applications of chemicals to control weeds, said Arthur Erickson, CEO and cofounder of Hylio, a Richmond, Texas-based company that produces agricultural drones.
“What tractors can’t do is spot treatment,” Erickson said. “Once the crop has started growing and it’s showing signs of fungus outbreak or some sort of weed outbreak in different sections of the field, you can’t go out there and isolate those spots and just spray that. You have to come in and spray everything—a shot-gun approach.”
This indiscriminate approach not only causes farmers to overspray pesticides, but it also carries health and environmental risks because of pesticide drift, the movement of pesticide dust or droplets through the air.
Continue reading: https://insideunmannedsystems.com/u-s-farms-embrace-drone-technology-benefits/

An Australian regulator on Wednesday ordered U.S. facial recognition software company Clearview AI Inc to stop collecting images from websites and destroy data collected in the country after an investigation found it breached privacy laws.
Privately owned Clearview, which cross-references photos scraped from social media websites with a database of billions of images, collected Australians' sensitive information without consent and without checking its matches were accurate, the Office of the Australian Information Commissioner (OAIC) said.
The finding shows a growing backlash by regulators against the controversial technology, which is being used or tested by law enforcement agencies around the world. In June, a Canadian regulator found that country's police broke the law by using Clearview's technology until it was banned there.
The OAIC is investigating the Australian Federal Police (AFP) over a trial of Clearview software it ran between October 2019 and March 2020. The office added on Wednesday that it was still finalising that investigation.
Continue reading: https://www.reuters.com/business/cop/australia-says-us-facial-recognition-software-firm-clearview-breached-privacy-2021-11-03/

“We need to be an AI-enabled company.” Replace the “AI” with any technology from history and this comment becomes a common refrain across businesses lured by the promises of new technology and fueled by FOMO (a fear of missing out). As enterprise strategists and former CXOs who have lived through many “technology is the solution, now what was the problem?” conversations, we talk extensively about this issue. To paraphrase Roy Amara, we overestimate the impact of a new technology early on. When it falls short of our expectations, our disappointment means we are less willing to adopt it when it is truly ready. The reality is that often it is only when we change how we operate and organize that many new technologies come into their own.
But what happens when we really combine organizational change and technology in the guise of artificial intelligence? Whilst companies are only starting to see what’s truly possible, they are discovering previously unattainable insights into their customers, employees, financials, environment, new products, and more. The accessibility of cloud-based technology and the nexus of engineering, mathematics, and organizational change promise solutions or improvements to our most complex issues ranging from climate change and poverty to criminal exploitation and disease. Many of our current use cases seem mundane in comparison with what the future holds, but new technology is still fueling business value into the trillions of dollars. Whether it’s a restaurant’s menu board customized to your locality, precise metrics about your favorite sports team, customized retail or banking offerings delivered to your phone, or the faster discovery of medical interventions, the promise of applying sophisticated technology to data has the power to amaze us and our customers.
So, if we take a rational, step-by-step approach to AI, where should we start so that we can truly capitalize on its potential? How do we position ourselves to identify and scale opportunities, while preventing ourselves from going down blind alleys? At the risk of sounding repetitive, many of the steps are the same as with any new technology. Let me share some basic steps any company can take—and are probably already taking—to learn how AI can supercharge their business by fully capitalizing on the data they already have.
Educate
History is littered with examples of new technologies that were either treated as a dark art that must be left to the wizard we now call the CIO to figure out, or as a magic spell that with a sprinkling of pixie dust will transform an organization merely by uttering its name. Understanding that AI is an enabler, not an outcome, education from the C-suite down is important. Dispelling myths behind AI and foundational components helps ground everyone in the considerations that are needed when thinking of applying AI to a business problem or opportunity. Don’t take for granted that everyone (or anyone) knows what AI and its sub-disciplines are. For the sake of clarity, AI encompasses the use of systems to perform tasks that usually require human intelligence. This is defined in a very narrow way, unlike what is referred to as “artificial general intelligence,” which aims to replicate human behavior but is just a distant dream. Most AI is based on machine learning to create a model that represents the decision process required often by divining patterns in data.
Continue reading: https://www.forbes.com/sites/amazonwebservices/2021/11/04/making-artificial-intelligence-real/?sh=4f98bef078b1

Establishing strong data environments and strategies will be key to the adoption of artificial intelligence in the military, according to Lt. Gen. Michael Groen, the director of the Joint Artificial Intelligence Center at the Defense Department.
Speaking in a webinar Wednesday on Federal News Network, Groen painted a picture of AI within DOD, emphasizing the need to cultivate an infrastructure that can handle a dynamic data environment. 
Groen described acquisition of AI technologies as a “generational transformation” that would take time, beginning with shifting DOD from a hardware-centric organization to a “world class software organization.
“Getting our data strategies together is a really important component,” he said. A major part of this will be changing the data ecosystem that DOD employs, specifically in regard to installing a common data environment to facilitate AI usage throughout the department.
Common data standards will help facilitate cross-departmental data collection and sharing. This in turn will help different DOD departments make operational decisions, including in combat.
“If 10 of 10 organizations can fire on the target you’ve identified, how do you decide which one actually should do that so that the other nine can save their ammo?” Groen said.
Groen confirmed that this work has yet to be done, and hinges on strong data pipelines.  
“As we build and grow and now start to get to a cohesive enterprise, a professional enterprise that’s predictable and trackable and has metrics, then we’re really going to be somewhere,” he said. 
DOD’s implementation of more advanced software can help curate and organize the influx of data coming into the department, creating a dynamic data environment that can take the input data and make recommendations and insights with sophisticated algorithms. 
Continue reading: https://www.nextgov.com/emerging-tech/2021/11/defense-ai-efforts-hinge-strong-data-environments/186635/

Ballyhooed artificial-intelligence technique known as “deep learning” revives 70-year-old idea.
In the past 10 years, the best-performing artificial-intelligence systems — such as the speech recognizers on smartphones or Google’s latest automatic translator — have resulted from a technique called “deep learning.”
Deep learning is in fact a new name for an approach to artificial intelligence called neural networks, which have been going in and out of fashion for more than 70 years. Neural networks were first proposed in 1944 by Warren McCullough and Walter Pitts, two University of Chicago researchers who moved to MIT in 1952 as founding members of what’s sometimes called the first cognitive science department.
Neural nets were a major area of research in both neuroscience and computer science until 1969, when, according to computer science lore, they were killed off by the MIT mathematicians Marvin Minsky and Seymour Papert, who a year later would become co-directors of the new MIT Artificial Intelligence Laboratory.
he technique then enjoyed a resurgence in the 1980s, fell into eclipse again in the first decade of the new century, and has returned like gangbusters in the second, fueled largely by the increased processing power of graphics chips.
“There’s this idea that ideas in science are a bit like epidemics of viruses,” says Tomaso Poggio, the Eugene McDermott Professor of Brain and Cognitive Sciences at MIT, an investigator at MIT’s McGovern Institute for Brain Research, and director of MIT’s Center for Brains, Minds, and Machines. “There are apparently five or six basic strains of flu viruses, and apparently each one comes back with a period of around 25 years. People get infected, and they develop an immune response, and so they don’t get infected for the next 25 years. And then there is a new generation that is ready to be infected by the same strain of virus. In science, people fall in love with an idea, get excited about it, hammer it to death, and then get immunized — they get tired of it. So ideas should have the same kind of periodicity!”
Weighty matters
Neural nets are a means of doing machine learning, in which a computer learns to perform some task by analyzing training examples. Usually, the examples have been hand-labeled in advance. An object recognition system, for instance, might be fed thousands of labeled images of cars, houses, coffee cups, and so on, and it would find visual patterns in the images that consistently correlate with particular labels.
Continue reading: https://scitechdaily.com/deep-learning-ai-explained-neural-networks/

So, we’ve seen some amazing light shows, but this one really takes la tarta. The giant skull wearing a sombrero during the Day of the Dead celebrations is really spectacular. If only this drone light show was real…
Anyone spotting this giant skull floating above Mexico city early this month would not only be fortunate, they’d have to have eaten the right type of mushrooms. The image has been circulating around the internet for at least a year. But it’s had new traction since the November 1 celebrations. The picture has been retweeted more than 38,000 times.
However, it’s not a light show. They’re not drones. It’s not even Mexico.
Snopes spotted it as a work of digital art, as physical as the page you’re reading. Yes, the drone lights aren’t quite distinct. (You can tell by the pixels.) And it does appear a little too gargantuan, even for a Mexican sky. And yes, that’s Mount Fuji in the background.
If only this drone light show was real
Japan’s sacred mountain does tend to give the game away.
Snopes actually tracked down the source of the mountain picture. It’s from a photograph taken by Flickr user Koshi Chiba in 2014.
The source of the city picture and the skull are still a mystery. Perhaps it didn’t start out as a hoax, but was just some Photoshop artist’s wish fulfilment. But it’s out there wild on the internet now, fooling people who don’t visit the Snopes debunking site often enough.
Continue reading: https://dronedj.com/2021/11/03/wait-fake-drone-shows-are-a-thing/

Flying a drone is one of the easiest, and now cheapest, ways to get a bird's eye view of almost anything. Yet as more people catch the drone bug, those unmanned aircraft are showing up where they shouldn't.
"Drones can cause major concerns for aircraft, not just helicopters, but fixed wings, especially smaller aircraft," says helicopter pilot Dan Oppenheim, who flies LiveCopter 3 for KCRA.
He's been flying for more than a decade and says that unmanned equipment like drones are becoming more of a worry for people in the air.
"It might not sound like a big deal," Oppenheim said, "But for perspective, if you take a drone that weighs about as much as a cell phone, think about the damage that might be caused if you were to take a cellphone and throw it off an overpass and hit a car at highway speeds. Well, drones are heavier than a cellphone. And we're generally increased flight faster than highway speed. So it can cause major damage."
When Oppenheim says major damage, the realities are stark. An Army Blackhawk helicopter took some major damage in 2017 while patrolling over the New York area in 2017. The collision and damage sparked an FAA and NHTSA investigation.

A drone that crashed near a Pennsylvania power substation last year was likely meant to damage or disrupt the electric equipment, according to a federal law enforcement bulletin obtained by CNN.
The July 2020 incident is the first known case of a "modified unmanned aircraft system likely being used in the United States to specifically target energy infrastructure," states the October 28 memo from the FBI, Department of Homeland Security and the National Counterterrorism Center. That statement is based on a review of drone incidents dating back to 2017.
No damage was done to the electricity supply or equipment, according to the memo. It is still unclear who was responsible for operating the drone that crashed on a rooftop near the unidentified substation.
Federal officials say they are distributing the intelligence bulletin now to state and local officials to raise awareness about the incident and the general threat of drones to critical infrastructure.
ABC News was first to report on the intelligence bulletin.
Whoever modified the drone likely tried to create a "short circuit to cause damage to transformers or distribution lines, based on the design and recovery location," the intelligence memo says. The drone "appeared to be heavily worn, indicating it was flown previously and was modified for this single flight."
Continue reading: https://www.cnn.com/2021/11/04/politics/drone-pennsylvania-electric-substation/index.html

Connecting your things, be they heavy metal or your fridge, to the internet is one thing, but what about unlocking the value of their location as well? Combining intelligence between people, places and things to understand and minimize risk.
The concept of the “internet of things” (IOT) is not a new one. It first started to gain some popularity in the Northern Hemisphere in the summer of 2010. The initial craze was when information leaked that Google's StreetView service had not only made 360-degree pictures, but had also stored tons of data of people's WiFi networks.
The internet was on fire with speculation as to whether this was the start of a Google strategy to not only index the internet but also index the physical world. Later that same year, the Chinese government announced it was going to make IOT one of its strategic priorities in its five-year plan.
No self-respecting tech commentator would be able to look themselves in the mirror if they didn’t mention the Gartner Hype Cycle for emerging technologies (which incidentally was invented in 2011). It included IOT as a new emerging phenomenon on its list.
Continue reading: https://www.itweb.co.za/content/4r1lyMRbLDXMpmda