South Korea's military drones fly in formation during a joint military drill with the US at Seungjin Fire Training Field in Pocheon on May 25, 2023. YELIM LEE

The deployment of AI-controlled drones that can make autonomous decisions about whether to kill human targets is moving closer to reality, The New York Times reported.

Lethal autonomous weapons, that can select targets using AI, are being developed by countries including the US, China, and Israel.

The use of the so-called "killer robots" would mark a disturbing development, say critics, handing life and death battlefield decisions to machines with no human input.

Several governments are lobbying the UN for a binding resolution restricting the use of AI killer drones, but the US is among a group of nations which also includes Russia, Australia, and Israel who are resisting any such move, favoring a non-binding resolution instead, The Times reported.

"This is really one of the most significant inflection points for humanity," Alexander Kmentt, Austria's chief negotiator on the issue, told The Times. "What's the role of human beings in the use of force it's an absolutely fundamental security issue, a legal issue and an ethical issue."

The Pentagon is working toward deploying swarms of thousands of AI-enabled drones, according to a notice published earlier this year.

In a speech in August, US Deputy Secretary of Defense, Kathleen Hicks, said technology like AI-controlled drone swarms would enable the US to offset China's People's Liberation Army's (PLA) numerical advantage in weapons and people.

"We'll counter the PLA's mass with mass of our own, but ours will be harder to plan for, harder to hit, harder to beat," she said, reported Reuters.

Frank Kendall, the Air Force secretary, told The Times that AI drones will need to have the capability to make lethal decisions while under human supervision.

"Individual decisions versus not doing individual decisions is the difference between winning and losing and you're not going to lose," he said.

"I don't think people we would be up against would do that, and it would give them a huge advantage if we put that limitation on ourselves."

The New Scientist reported in October that AI-controlled drones have already been deployed on the battlefield by Ukraine in its fight against the Russian invasion, though it's unclear if any have taken action resulting in human casualties.

The Pentagon did not immediately respond to a request for comment.

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US closer to using AI-drones that can autonomously decide to kill humans - Business Insider

NATIONAL HARBOR, Md. -- Artificial intelligence employed by the U.S. military has piloted pint-sized surveillance drones in special operations forces missions and helped Ukraine in its war against Russia. It tracks soldiers fitness, predicts when Air Force planes need maintenance and helps keep tabs on rivals in space.

Now, the Pentagon is intent on fielding multiple thousands of relatively inexpensive, expendable AI-enabled autonomous vehicles by 2026 to keep pace with China. The ambitious initiative dubbed Replicator seeks to galvanize progress in the too-slow shift of U.S. military innovation to leverage platforms that are small, smart, cheap, and many, Deputy Secretary of Defense Kathleen Hicks said in August.

While its funding is uncertain and details vague, Replicator is expected to accelerate hard decisions on what AI tech is mature and trustworthy enough to deploy - including on weaponized systems.

There is little dispute among scientists, industry experts and Pentagon officials that the U.S. will within the next few years have fully autonomous lethal weapons. And though officials insist humans will always be in control, experts say advances in data-processing speed and machine-to-machine communications will inevitably relegate people to supervisory roles.

Thats especially true if, as expected, lethal weapons are deployed en masse in drone swarms. Many countries are working on them and neither China, Russia, Iran, India or Pakistan have signed a U.S.-initiated pledge to use military AI responsibly.

Its unclear if the Pentagon is currently formally assessing any fully autonomous lethal weapons system for deployment, as required by a 2012 directive. A Pentagon spokeswoman would not say.

Paradigm shifts

Replicator highlights immense technological and personnel challenges for Pentagon procurement and development as the AI revolution promises to transform how wars are fought.

"The Department of Defense is struggling to adopt the AI developments from the last machine-learning breakthrough, said Gregory Allen, a former top Pentagon AI official now at the Center for Strategic and International Studies think tank.

The Pentagon's portfolio boasts more than 800 AI-related unclassified projects, much still in testing. Typically, machine-learning and neural networks are helping humans gain insights and create efficiencies.

The AI that weve got in the Department of Defense right now is heavily leveraged and augments people, said Missy Cummings, director of George Mason Universitys robotics center and a former Navy fighter pilot. Theres no AI running around on its own. People are using it to try to understand the fog of war better.

Space, war's new frontier

One domain where AI-assisted tools are tracking potential threats is space, the latest frontier in military competition.

China envisions using AI, including on satellites, to "make decisions on who is and isnt an adversary, U.S. Space Force chief technology and innovation officer Lisa Costa, told an online conference this month.

The U.S. aims to keep pace.

An operational prototype called Machina used by Space Force keeps tabs autonomously on more than 40,000 objects in space, orchestrating thousands of data collections nightly with a global telescope network.

Machina's algorithms marshal telescope sensors. Computer vision and large language models tell them what objects to track. And AI choreographs drawing instantly on astrodynamics and physics datasets, Col. Wallace Rhet Turnbull of Space Systems Command told a conference in August.

Another AI project at Space Force analyzes radar data to detect imminent adversary missile launches, he said.

Maintaining planes and soldiers

Elsewhere, AI's predictive powers help the Air Force keep its fleet aloft, anticipating the maintenance needs of more than 2,600 aircraft including B-1 bombers and Blackhawk helicopters.

Machine-learning models identify possible failures dozens of hours before they happen, said Tom Siebel, CEO of Silicon Valley-based C3 AI, which has the contract. C3's tech also models the trajectories of missiles for the the U.S. Missile Defense Agency and identifies insider threats in the federal workforce for the Defense Counterintelligence and Security Agency.

Among health-related efforts is a pilot project tracking the fitness of the Army's entire Third Infantry Division more than 13,000 soldiers. Predictive modeling and AI help reduce injuries and increase performance, said Maj. Matt Visser.

Aiding Ukraine

In Ukraine, AI provided by the Pentagon and its NATO allies helps thwart Russian aggression.

NATO allies share intelligence from data gathered by satellites, drones and humans, some aggregated with software from U.S. contractor Palantir. Some data comes from Maven, the Pentagons pathfinding AI project now mostly managed by the National Geospatial-Intelligence Agency, say officials including retired Air Force Gen. Jack Shanahan, the inaugural Pentagon AI director,

Maven began in 2017 as an effort to process video from drones in the Middle East spurred by U.S. Special Operations forces fighting ISIS and al-Qaeda and now aggregates and analyzes a wide array of sensor- and human-derived data.

AI has also helped the U.S.-created Security Assistance Group-Ukraine help organize logistics for military assistance from a coalition of 40 countries, Pentagon officials say.

All-Domain Command and Control

To survive on the battlefield these days, military units must be small, mostly invisible and move quickly because exponentially growing networks of sensors let anyone see anywhere on the globe at any moment, then-Joint Chiefs chairman Gen. Mark Milley observed in a June speech. And what you can see, you can shoot.

To more quickly connect combatants, the Pentagon has prioritized the development of intertwined battle networks called Joint All-Domain Command and Control to automate the processing of optical, infrared, radar and other data across the armed services. But the challenge is huge and fraught with bureaucracy.

Christian Brose, a former Senate Armed Services Committee staff director now at the defense tech firm Anduril, is among military reform advocates who nevertheless believe they "may be winning here to a certain extent."

The argument may be less about whether this is the right thing to do, and increasingly more about how do we actually do it -- and on the rapid timelines required," he said. Brose's 2020 book, The Kill Chain, argues for urgent retooling to match China in the race to develop smarter and cheaper networked weapons systems.

To that end, the U.S. military is hard at work on "human-machine teaming." Dozens of uncrewed air and sea vehicles currently keep tabs on Iranian activity. U.S. Marines and Special Forces also use Andurils autonomous Ghost mini-copter, sensor towers and counter-drone tech to protect American forces.

Industry advances in computer vision have been essential. Shield AI lets drones operate without GPS, communications or even remote pilots. It's the key to its Nova, a quadcopter, which U.S. special operations units have used in conflict areas to scout buildings.

On the horizon: The Air Forces loyal wingman program intends to pair piloted aircraft with autonomous ones. An F-16 pilot might, for instance, send out drones to scout, draw enemy fire or attack targets. Air Force leaders are aiming for a debut later this decade.

The race to full autonomy

The loyal wingman timeline doesn't quite mesh with Replicator's, which many consider overly ambitious. The Pentagon's vagueness on Replicator, meantime, may partly intend to keep rivals guessing, though planners may also still be feeling their way on feature and mission goals, said Paul Scharre, a military AI expert and author of Four Battlegrounds.

Anduril and Shield AI, each backed by hundreds of millions in venture capital funding, are among companies vying for contracts.

Nathan Michael, chief technology officer at Shield AI, estimates they will have an autonomous swarm of at least three uncrewed aircraft ready in a year using its V-BAT aerial drone. The U.S. military currently uses the V-BAT -- without an AI mind -- on Navy ships, on counter-drug missions and in support of Marine Expeditionary Units, the company says.

It will take some time before larger swarms can be reliably fielded, Michael said. Everything is crawl, walk, run -- unless youre setting yourself up for failure.

The only weapons systems that Shanahan, the inaugural Pentagon AI chief, currently trusts to operate autonomously are wholly defensive, like Phalanx anti-missile systems on ships. He worries less about autonomous weapons making decisions on their own than about systems that dont work as advertised or kill noncombatants or friendly forces.

The department's current chief digital and AI officer Craig Martell is determined not to let that happen.

Regardless of the autonomy of the system, there will always be a responsible agent that understands the limitations of the system, has trained well with the system, has justified confidence of when and where its deployable -- and will always take the responsibility, said Martell, who previously headed machine-learning at LinkedIn and Lyft. That will never not be the case.

As to when AI will be reliable enough for lethal autonomy, Martell said it makes no sense to generalize. For example, Martell trusts his car's adaptive cruise control but not the tech thats supposed to keep it from changing lanes. As the responsible agent, I would not deploy that except in very constrained situations, he said. Now extrapolate that to the military.

Martells office is evaluating potential generative AI use cases it has a special task force for that but focuses more on testing and evaluating AI in development.

One urgent challenge, says Jane Pinelis, chief AI engineer at Johns Hopkins Universitys Applied Physics Lab and former chief of AI assurance in Martells office, is recruiting and retaining the talent needed to test AI tech. The Pentagon can't compete on salaries. Computer science PhDs with AI-related skills can earn more than the military's top-ranking generals and admirals.

Testing and evaluation standards are also immature, a recent National Academy of Sciences report on Air Force AI highlighted.

Might that mean the U.S. one day fielding under duress autonomous weapons that dont fully pass muster?

We are still operating under the assumption that we have time to do this as rigorously and as diligently as possible, said Pinelis. I think if were less than ready and its time to take action, somebody is going to be forced to make a decision.

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Pentagon's AI initiatives accelerate hard decisions on lethal autonomous weapons. - ABC News

Last month President Joe Biden issued an executive order on artificial intelligence, the governments most ambitious attempt to set ground rules for this technology. The order focuses on establishing best practices and standards for AI models, seeking to constrain Silicon Valleys propensity to release products before theyve been fully tested to move fast and break things.

But despite the orders scope its 111 pages and covers a range of issues, including industry standards and civil rights two glaring omissions may undermine its promise.

The first is that the order fails to address the loophole provided by Section 230 of the Communications Decency Act. Much of the consternation surrounding AI has to do with the potential for deep fakes convincing video, audio and image hoaxes and misinformation. The order does include provisions for watermarking and labeling AI content so people at least know how its been generated. But what happens if the content is not labeled?

Much of the AI-generated content will be distributed on social media sites such as Instagram and X (formerly Twitter). The potential harm is frightening: Already theres been a boom of deep fake nudes, including of teenage girls. Yet Section 230 protects platforms from liability for most content posted by third parties. If the platform has no liability for distributing AI-generated content, what incentive does it have to remove it, water-marked or not?

Imposing liability only on the producer of the AI content, rather than on the distributor, will be ineffective at curbing deep fakes and misinformation because the content producer may be hard to identify, out of jurisdictional bounds or unable to pay if found liable. Shielded by Section 230, the platform may continue to spread harmful content and may even receive revenue for it if its in the form of an ad.

A bipartisan bill sponsored by Sens. Richard Blumenthal, D-Conn., and Josh Hawley, R-Mo., seeks to address this liability loophole by removing 230 immunity for claims and charges related to generative artificial intelligence. The bill does not, however, seem to resolve the question of how to apportion responsibility between the AI companies that generate the content and the platforms that host it.

The second worrisome omission from the AI order involves terms of service, the annoying fine print that plagues the internet and pops up with every download. Although most people hit accept without reading these terms, courts have held that they can be binding contracts. This is another liability loophole for companies that make AI products and services: They can unilaterally impose long and complex one-sided terms allowing illegal or unethical practices and then claim we have consented to them.

In this way, companies can bypass the standards and best practices set by advisory panels. Consider what happened with Web 2.0 (the explosion of user-generated content dominated by social media sites). Web tracking and data collection were ethically and legally dubious practices that contravened social and business norms. Facebook, Google and others, however, could defend themselves by claiming that users consented to these intrusive practices when they clicked to accept the terms of service.

In the meantime, companies are releasing AI products to the public, some without adequate testing and encouraging consumers to try out their products for free. Consumers may not realize that their free use helps train these models and so their efforts are essentially unpaid labor. They also may not realize that they are giving up valuable rights and taking on legal liability.

For example, Open AIs terms of service state that the services are provided as is, with no warranty, and that the user will defend, indemnify, and hold harmless Open AI from any claims, losses, and expenses (including attorneys fees) arising from use of the services. The terms also require the user to waive the right to a jury trial and class action lawsuit. Bad as such restrictions may seem, they are standard across the industry. Some companies even claim a broad license to user-generated AI content.

Bidens AI order has largely been applauded for trying to strike a balance between protecting the public interest and innovation. But to give the provisions teeth, there must be enforcement mechanisms and the threat of lawsuits. The rules to be established under the order should limit Section 230 immunity and include standards of compliance for platforms. These might include procedures for reviewing and taking down content, mechanisms to report issues within the company and externally, and minimum response times from companies to external concerns. Furthermore, companies should not be allowed to use terms of service (or other forms of consent) to bypass industry standards and rules.

We should heed the hard lessons from the last two decades to avoid repeating the same mistakes. Self-regulation for Big Tech simply does not work, and broad immunity for profit-seeking corporations creates socially harmful incentives to grow at all costs. In the race to dominate the fiercely competitive AI space, companies are almost certain to prioritize growth and discount safety. Industry leaders have expressed support for guardrails, testing and standardization, but getting them to comply will require more than their good intentions it will require legal liability.

Nancy Kim is a law professor at Chicago-Kent College of Law, Illinois Institute of Technology.

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Commentary: Biden's executive order on AI is ambitious and ... - The Spokesman Review

Founder of Laulau-During the UK's 2023 cost-of-living crisis, He launched the Hot Meal Challenge to raise hot meals for Londoners facing food poverty. Under the patronage of Lord Woolley of Woodford and in partnership with Sufra, this social fundraiser supported hundreds of families across London.Fabio Richter

In an era marked by economic challenges, the resilience of human generosity is more evident than ever. The charity and non-profit organizations (NGOs) market has seen incredible growth, reaching US$305.2 billion in 2023 from US$288.97 billion in 2022. And the projections are even more promising, with estimates of the market reaching US$369.21 billion by 2027. Notably, Generation Z, born between 1997 and 2012, has contributed increasingly to this philanthropic surge. Despite their relatively lesser financial resources, studies show that Gen Z's charitable contributions are growing, reflecting their commitment to social and environmental causes. Recent data reveals that Generation Z, though younger and with comparatively less wealth, contributes significantly to this trend. This growth, amidst a weakened global economy, rising prices, and geopolitical volatility, underscores a collective commitment to positive impact.

Concurrently, there is a surge in the utility and popularity of AI adoption worldwide. The convergence of these two trendsexpanding NGO market and AI technologiesholds immense potential, as philanthropy proactively leverages AI's innovative capabilities. Experts in the field, such as James Hodson, also CEO of AI for Good Foundation, suggest that AI can revolutionize fundraising and operational efficiency in philanthropy, creating more impact per dollar donated, as evident in Lifeforce, a Humanitarian Aid 2.0 initiative.

While much has been discussed regarding AI's economic impact, with estimations from PWC of up to US$15.7 trillion added to the global economy by 2030, its potential influence on humanitarian action still needs to be explored.

While AI's economic impact is well-documented, its potential in humanitarian sectors is just starting to be realized. Emerging technologies can drive further innovation in the philanthropic sector, benefiting charities through personalized donor outreach strategies, optimized resource allocation, and streamlined decision-making processes. For example, the American Red Cross has implemented AI algorithms to predict donation trends, enabling them to allocate resources more effectively during crises.

While AI's economic impact is well-documented, its potential in humanitarian sectors is just starting to be realized. AI can revolutionize philanthropy with personalized donor outreach, optimized resource allocation, and more efficient decision-making.

For instance, Save The Children Australia enhanced donor outreach with AI-powered predictions, using data segmentation and their CRM system for effective donor targeting. They ranked donation profiles to target specific donors effectively. Similarly, Greenpeace Australia Pacific leveraged machine learning techniques to improve donor retention through a churn propensity model. By assigning scores to previous donation histories, the charity identified donors to re-engage successfully. Furthermore, SwissFoundations highlights the unexplored potential of AI in donor matching, reporting, impact evaluation, and increasing transparency and accountability within philanthropic organizations. These case studies illustrate how AI can provide actionable insights into donor behavior, leading to more targeted and successful fundraising strategies.

Gen Z is uniquely positioned to advance charitable work with their digital fluency and social media savviness. As digital natives, Gen Z brings a unique perspective to philanthropy. In addition to AI, the untapped potential of Gen Z, born between 1997 and 2012, can drive advancements in charitable work through new technologies. As the world's first generation of authentic digital natives, Their comfort with technology and social media paves the way for innovative approaches to charitable giving.

The intersection of AI and Gen Z presents a unique opportunity to shape the future of philanthropy. As these two forces continue to converge, the possibilities for innovation and positive impact are boundless. Research indicates that Gen Z donors prefer digital platforms for charitable engagement and are more likely to support causes that align with their values, emphasizing the need for NGOs to adapt to these preferences. This generation is more than just digitally competent; they are socially conscious. According to a study by McKinsey, 70% of Gen Z prioritize social impact in their spending and charitable giving, indicating a shift towards more conscientious consumerism.

Dubious stereotypes often dismiss Gen Z as a generation of self-absorbed and distractible youth, seemingly trapped by the addictive allure of social media and limited in their ability to appreciate the world beyond their personal experiences. However, according to a Forbes article in 2022, members of Gen Z are defying these expectations and emerging as the next generation of charitable donors, potentially surpassing their older counterparts in their willingness to support philanthropic causes. Their motivations stem from a deep sense of conviction.

Gen Z distinguishes itself as a charitable demographic and takes the lead in its chosen advocacies, spearheading digitally driven efforts to address philanthropic causes. The Hot Meal Challenge is a prime example of how Gen Z's digital savviness can be harnessed for philanthropic efforts. It also exemplifies Gen Z's philanthropic innovation, addressing food insecurity in the UK. Hot Meal Challenge is a viral fundraising campaign aimed at tackling the United Kingdom's pervasive cost-of-living crisis by providing hot meals to food-insecure households. Collaborating with Sufra, a prominent London-based food poverty charity, Gen Z members nominate each other via an app to donate hot meals.

Fabio Richter, the founder of the Hot Meal Challenge, firmly believes that philanthropy can drive meaningful global change, especially when harnessed with the power of technology. He states, "Through strategic giving and thoughtful investments, philanthropy can catalyze positive transformations in society. To fully unlock its potential, it is crucial to leverage technology, invest in local capacity-building, and collaborate with policymakers to enact long-term structural change."

Fabio emphasizes that Gen Z represents a highly promising donor market with which charities and non-governmental organizations (NGOs) should actively engage. "Surprisingly, non-profits often overlook generational cohorts like Gen Z and Millennials. While they may have less purchasing power compared to older generations, they outperform them in terms of annualized giving rates as a percentage of disposable income," he explains. "To effectively connect with younger generations, nonprofits must understand them from multiple dimensionsdemographically, behaviorally, and psychographically." This viral campaign brought widespread attention to food insecurity issues in the UK, demonstrating the power of social media in driving social change.

Gen Z challenges the prevailing stereotypes by actively contributing to philanthropic endeavors. Their digital savvy and deep commitment to causes make them a force to be reckoned with. Nonprofits and organizations should recognize the untapped potential of this emerging market and develop comprehensive strategies to engage and collaborate with Gen Z effectively. Fabio Richter, the founder, stated, "The success of this initiative is a testament to Gen Z's commitment to social change, harnessed through technology." Richter's approach in the Hot Meal Challenge exemplifies how combining technology with a deep understanding of Gen Z's communication styles can lead to successful philanthropic campaigns.

While AI offers numerous benefits, it also presents new challenges in terms of ethics and privacy. Balancing these aspects is crucial for sustainable growth in philanthropy. As AI technology holds immense promise in revolutionizing humanitarian work, advocates and supporters must remain vigilant about the inherent risks associated with emerging technologies. Managing the potential systemic risks posed by training AI systems, addressing the challenges of predictive decision-making, and ensuring transparency are all paramount. Fabio, an expert in the field, highlights the importance of preventing AI systems from perpetuating and exacerbating structural biases inherent in data.

When deployed carefully and strategically, AI can be an extraordinary catalyst for transforming humanitarian efforts, regardless of their humble origins. Pioneering digital philanthropic initiatives such as the Hot Meal Challenge are already reshaping the industry landscape and paving the way for tangible real-world impact. Speaking at the initiative's launch, Lord Woolley of Woodford emphasized its transformative potential in fighting poverty and restoring human dignity.

It's vital for organizations to establish ethical guidelines for AI use, ensuring that these technologies are used responsibly and transparently, with a focus on enhancing rather than replacing human decision-making in philanthropy. Ethical considerations, like data privacy and bias in AI algorithms, are crucial. Measures such as transparent AI development processes and regular ethical audits are essential to ensure these tools serve the greater good without unintended consequences. It is critical to remember that integrating AI and philanthropy must be rooted in fundamental human values underpinning charitable endeavors: service, compassion, and a steadfast commitment to envisioning a better future. As Lord Woolley aptly stated, this endeavor is not just about individual gain but collective action and collaboration in serving others.

The collaboration between AI and philanthropy has the power to drive significant change. Still, it must always be guided by a deep understanding of human values and a shared vision for a brighter tomorrow.

The intersection of AI and Gen Z presents a unique opportunity to shape the future of philanthropy. The convergence of AI, Gen Z values, and philanthropy is a powerful combination with the potential to reshape humanitarian efforts.

As these complementary forces gain momentum, upholding ethical integrity and managing risks becomes paramount to unlocking innovative potential. By embracing these trends, NGOs can unlock new potentials for impact and efficiency.

This approach promises technological advancement and a more compassionate and efficient philanthropic sector.

Moving forward, it is essential for philanthropic organizations to stay attuned to these technological advancements and generational shifts, ensuring that their strategies remain relevant and effective in the evolving landscape of philanthropy. The synergistic potential of this unique convergence still needs to be explored. This approach promises technological advancement and a more compassionate and efficient philanthropic sector. With courage, care, and conviction, AI and Gen Z have the opportunity to shape the course of philanthropy for the future and the lasting ascent of humanity.

Mr. Minevich is a highly regarded and trusted Digital Cognitive Strategist, Artificial Intelligence expert, Venture Capitalist, and the principal founder of Going Global Ventures. Mark collaborates and advises large global enterprises both in the US and Japan (Hitachi), and is the official AI and Future of Work Advisor to the Boston Consulting Group. Currently, he serves as the strategic advisor and Global ambassador to the CEO and Chairman of New York based IPsoft Inc.

Mark holds the role of senior fellow as part of the U.S. Council on Competitiveness in Washington, D.C., and maintains a position as senior adviser on Global Innovation and Technology to the United Nations Office of Project Services (UNOPS). He is an appointed member of the G20/B20s Digital Task Force, supplementing the group with expert knowledge on digitization, advanced autonomous systems, and the future of AI.

Mark is also the founder and Co-Chair of the World Artificial Intelligence Organization and AI Pioneers based in New York, and was appointed as the Global Digital Ambassador to the World Assessment Council in early 2020. He is the Strategic Advisor to SwissCognitive - "independent" Global AI think-tank in Switzerland, which aims to share, connect, and unlock the fullest potential of Artificial Intelligence.

Mark also advises several venture capital groups. He acts as a Fund Adviser to Bootstrap Labs based in San Francisco: a pioneer in the realm of VC funds focused on applied AI, carrying with it a mature fund and portfolio of 24 applied AI companies. Mark is also an Advisor to the AI Capital Venture Fund based in Colorado, which is a dedicated venture and private equity fund geared towards AI companies in the late-seed to growth-stage maturity level.

Mark is also a trusted Adviser and Entrepreneur in Residence for Hanaco Ventures, a global venture fund that focuses on late-stage, pre-IPO Israeli and US companies powered by bold, visionary, and passionate minds. Prior to this position, Mark was the Vice Chair of Ventures and External Affairs, as well as CTO at the Comtrade Group, an international technology conglomerate. He also served as the CTO and Strategy Executive at IBM, and held other management, technology, and strategy roles that entailed formulating investment tactics for Venture Capital Incubation programs.

Mark is also involved in media and journalism, and contributes to a number of publications, such as Forbes.com. His knowledge has been cited and his name has been featured in articles on an international scale.

Forbes named Mark one of the Leaders to Watch in 2017. He has received the Albert Einstein Award for Outstanding Achievement and the World Trade Leadership Award from the World Trade Centers and World Trade Centers Association. Mark has served as a venture partner with GVA Capital in Silicon Valley, advising the fund on AI startups. He has also served as venture advisor to Global Emerging Markets, an alternative investment group that manages a diverse set of investment vehicles. Mark was also involved with Research Board, a Gartner company and international think-tank advising CIOs at some of the worlds largest corporations, such as: Deutsche Bank, BTM Corporation, Geotek Communications, Qwest Communications, Comcast, and USWEB/CKS.

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AI And Generation Z: Pioneering A New Era Of Philanthropy - Forbes

Fovia Ai Provides Efficient AI Results in One Unified Viewer

CHICAGO, Nov. 26, 2023 /PRNewswire/ -- Fovia Ai, Inc., a subsidiary of Fovia, Inc., a world leader in advanced visualization for over two decades and a preeminent provider of zero-footprint, cloud-based imaging SDKs, today announced that it will be showcasing AI interaction and visualization of AI results from multiple vendors and algorithms displayed efficiently in one consistent user interface, in the Imaging Artificial Intelligence in Practice (IAIP) demonstration November 26 November 29 at the 109th Scientific Assembly and Annual Meeting of the Radiology Society of North America (RSNA 2023) at McCormick Place in Chicago.

RSNA attendees visiting the IAIP exhibit will be able to explore AI integrations from 20 exhibitors with 28 products that are based on real-world clinical scenarios as well as see live demonstrations of Fovia Ai software integrated with vendors including GE Healthcare, Hyperfine, Laurel Bridge, Milvue, Nuance, Nvidia, PaxeraHealth, Qure.ai, Qvera, Siemens Healthineers, Smart Reporting, Telerad Tech and Visage Imaging. The interactive exhibit provides attendees access to emerging AI technologies, demonstrates the interoperability standards needed to integrate AI into the workflow of diagnostic radiology, and highlights AI-driven products that remove barriers to clinical adoption.

"For the fourth year in a row, Fovia Ai is thrilled to participate in the IAIP demo and to provide optimized AI visualization for various industry partners. Acting as a gatekeeper for AI findings, our technology works conjointly with the latest interoperability standards to make physician-validated findings readily available to AI orchestrators, PACS, and reporting systems. At this year's RSNA we are also demonstrating the efficiency of visualizing and interacting with AI results in one consistent user interface regardless of the algorithm origin, thereby streamlining AI-supported image interpretation," stated Fovia Ai's Chief Technology Officer, Kevin Kreeger, Ph.D. "We are pleased with the incredible forward-thinking environment the collaborative IAIP team provides every year."

Conveniently located adjacent to the IAIP demonstration, attendees visiting the Fovia Ai booth (#4161), can:

To learn more about Fovia and Fovia Ai's complete product suites or arrange a demonstration at the 109th Scientific Assembly and Annual Meeting of the Radiological Society of North America, November 26November 29,contact us.

About Fovia Ai

Fovia Ai, Inc. is a subsidiary of Fovia, Inc., a world leader in advanced visualization, a preeminent provider of cloud-based, zero-footprint imaging SDKs, and the developer of High Definition Volume Rendering, XStream HDVR, F.A.S.T. RapidPrint and TruRender. Fovia Ai's flagship products, F.A.S.T. aiCockpit and F.A.S.T. AI SDK, enable radiologists and clinicians to efficiently access AI results directly within their existing workflows from any PACS, worklist, dictation software or hospital system. Complementary products in Fovia Ai's product suite include F.A.S.T. AI Annotation, F.A.S.T. AI Validation, F.A.S.T. AI Workflows, F.A.S.T. Interactive AI and F.A.S.T. Interactive Segmentation, collectively providing tools to annotate, validate, modify, accept/reject, interact with and segment data. The flexible architecture of Fovia Ai's product suite and Fovia's 20+ years of radiology integration experience facilitate seamless integrations with a variety of partners, platforms, processors and operating systems.

For additional information and to learn more about commercial, academic or research licensing, visit fovia.ai or fovia.com.

IMPORTANT REGULATORY NOTICE: The applications mentioned herein are for investigational use only at this time.

SOURCE Fovia Ai, Inc.

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Fovia Ai to Showcase Optimized AI Visualization at IAIP Exhibit ... - PR Newswire