#Ethical AI Deployment.

[mtariqniaz]

The Transformative Benefits of Artificial Intelligence

Title: The Transformative Benefits of Artificial Intelligence Artificial Intelligence (AI) has emerged as one of the most revolutionary technologies of the 21st century. It involves creating intelligent machines that can mimic human cognitive functions such as learning, reasoning, problem-solving, and decision-making. As AI continues to advance, its impact is felt across various industries and…

[ai-innova7ions]

Is AI Regulation Keeping Up? The Urgent Need Explained!

AI regulation is evolving rapidly, with governments and regulatory bodies imposing stricter controls on AI development and deployment. The EU's AI Act aims to ban certain uses of AI, impose obligations on developers of high-risk AI systems, and require transparency from companies using generative AI. This trend reflects mounting concerns over ethics, safety, and the societal impact of artificial intelligence. As we delve into these critical issues, we'll explore the urgent need for robust frameworks to manage this technology's rapid advancement effectively. Stay tuned for an in-depth analysis!

#AIRegulation

#EUAIACT

Video Automatically Generated by Faceless.Video

[jcmarchi]

California Assembly passes controversial AI safety bill

New Post has been published on https://thedigitalinsider.com/california-assembly-passes-controversial-ai-safety-bill/

California Assembly passes controversial AI safety bill

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The California State Assembly has approved the Safe and Secure Innovation for Frontier Artificial Intelligence Models Act (SB 1047).

The bill, which has sparked intense debate in Silicon Valley and beyond, aims to impose a series of safety measures on AI companies operating within California. These precautions must be implemented before training advanced foundation models.

Key requirements of the bill include:

Implementing mechanisms for swift and complete model shutdown

Safeguarding models against “unsafe post-training modifications”

Establishing testing procedures to assess the potential risks of models or their derivatives causing “critical harm”

Senator Scott Wiener, the primary author of SB 1047, said: “We’ve worked hard all year, with open source advocates, Anthropic, and others, to refine and improve the bill. SB 1047 is well calibrated to what we know about foreseeable AI risks, and it deserves to be enacted.”

SB 1047 — our AI safety bill — just passed off the Assembly floor. I’m proud of the diverse coalition behind this bill — a coalition that deeply believes in both innovation & safety.

AI has so much promise to make the world a better place. It’s exciting.

Thank you, colleagues.

— Senator Scott Wiener (@Scott_Wiener) August 28, 2024

The senator emphasised that the bill simply asks large AI laboratories to follow through on their existing commitments to test their extensive models for catastrophic safety risks.

However, the proposed legislation has faced opposition from various quarters, including AI companies OpenAI and Anthropic, politicians Zoe Lofgren and Nancy Pelosi, and California’s Chamber of Commerce. Critics argue that the bill places excessive focus on catastrophic harms and could disproportionately affect small, open-source AI developers.

In response to these concerns, several amendments were made to the original bill. These changes include:

Replacing potential criminal penalties with civil ones

Limiting the enforcement powers granted to California’s attorney general

Modifying requirements for joining the “Board of Frontier Models” created by the bill

The next step for SB 1047 is a vote in the State Senate, where it is expected to pass. Should this occur, the bill will then be presented to Governor Gavin Newsom, who will have until the end of September to make a decision on its enactment.

SB 1047 has passed the Assembly floor vote with support from both sides of the aisle. We need this regulation to give whistleblowers the protections they need to speak out on critical threats to public safety. Governor @GavinNewsom, you should sign SB 1047 into law.

— Lessig 🇺🇦 (@lessig) August 28, 2024

As one of the first significant AI regulations in the US, the passage of SB 1047 could set a precedent for future legislation. The outcome of this bill may have far-reaching implications for the AI industry, potentially influencing the development and deployment of advanced AI models not only in California but across the nation and beyond.

(Photo by Josh Hild)

See also: Chinese firms use cloud loophole to access US AI tech

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: ai, ai safety bill, artificial intelligence, california, ethics, law, legal, Legislation, sb 1047, Society, usa

[nationallawreview]

White House Publishes Steps to Protect Workers from the Risks of AI

Last year the White House weighed in on the use of artificial intelligence (AI) in businesses. Since the executive order, several government entities including the Department of Labor have released guidance on the use of AI. And now the White House published principles to protect workers when AI is used in the workplace. The principles apply to both the development and deployment of AI systems.…

[specialagentartemis]

Murderbot September Day 4: Holism/University of Mihira and New Tideland

The AI project that gave rise to ART, Holism, and half a dozen other super-intelligent AI ships were made under a fairly secretive government contract from the Mihiran and New Tideland governments. They wanted to encourage the University scientists to push the envelope of AI, to determine what AI could do - partially exploring the boundaries of ethical automated alternatives to human labor or construct use, partially to have some cutting-edge self-defense monitoring in case the corporate polities they share a system with tries to push them around.

(The government still hasn't really come around on "bots are people." That's something the AI lab scientists and ship crews all end up realizing themselves. The ships meanwhile are the property of the university. It's... complicated.)

Only a few AIs were approved for moving onto the final stage, deployment on ships and stations. (They had to be deployed somewhere like a ship or a station to push their full potential - ART and Holism have massive processors that need to be housed somewhere.) Upon being moved to a ship, the AI is allowed to name it. The name gets sent to the University administration for approval, of course. (They don't tell admin that the ship itself chose it. Let's not get into that.) There's no particular name theme for the ships, it's a reflection of whatever the AI loaded into them likes. Perihelion and Holism had a project designation number, a hard feed address, and various nicknames over the years, but when they were installed on the new ships, that's when they chose their ships' - and their - current names.

(Holism thinks Perihelion is a tunnel-visioned nerd for its choice; Perihelion thinks Holism is insufferably self-important for its.)

[emi-matchu]

lmaoooo the big Mozilla statement for the year is very very VERY AI, and only barely mentions Firefox, in the context of making it an exciting AI browser

We are embedding [tech to label product reviews as "fake"] into Firefox and will incorporate AI into the browser and other Mozilla products in ways that can provide real value to users. We see huge potential for AI, but it must be implemented in ways that serve the interests of people and not business. —Mozilla, "State of Mozilla 2023"

also lord help me this shit is so funny, here's their Exciting Business Model

like, look, I'm not saying there's not room in the space for an ethical approach for deploying AI tech—with a radically different approach to training data, regulation, and economic impact than practically all AI tech is using today

but Mozilla is not taking that approach; they're taking an approach that looks superficially "ethical" enough to carve out a niche for themselves as the cool popular good guys, as Mozilla always does

hate it here

(Also my apologies for the link to the statement, it's wildly difficult to use on mobile, I eventually gave up copy-pasting that text because it kept swiping me to other sections instead fml)

reads this then thinks some more about the recent uptick in the Mozilla savior narrative

Firefox certainly isn't scummy like e.g. Brave is now, but like. wanna give it another year or two and see about that?

(more thoughts and context below the cut)

my point here isn't to say that Firefox isn't the best option today in many cases; it's that any plan that doesn't include the fact that Mozilla is also low-key gross is setting people up for failure 😐😭

if you wanna be using a good safe browser, the only working model is to actively pay attention, and be prepared to hop every few years—as it is with all modern software (or to simply accept a certain amount of risk to your privacy & security because you're busy; that's reasonable and choosing the best browser for the greater good isn't a serious moral obligation imo)

currently this is my list of reasonable bets by platform:

Windows: Vivaldi, Firefox

Mac: Safari, Firefox

Linux: Chromium, Firefox

but like. the expiration date on that recommendation is end-of-2024, possibly sooner, depending on when the incentives of their product teams make the usual pivot from pro-user to anti-user

and I think Firefox is one of the most liable to turn earlier than expected, especially as they hurry to position themselves as AI leaders and actively reduce human input in web development…

(note too that I'm making these recs on the assumption that Vivaldi and Linux-packaged Chromium continue to have the ability to turn off or delete the scummiest new Chromium features—so far they've been reliably doing this, but it's possible that their capabilities might change in the coming years, as things get more baked in)

[leonaquitaine]

On the subject of generative AI

Let me start with an apology for deviating from the usual content, and for the wall of text ahead of you. Hopefully, it'll be informative, instructive, and thought-provoking. A couple days ago I released a hastily put-together preset collection as an experiment in 3 aspects of ReShade and virtual photography: MultiLUT to provide a fast, consistent tone to the rendered image, StageDepth for layered textures at different distances, and tone-matching (something that I discussed recently).

For the frames themselves, I used generative AI to create mood boards and provide the visual elements that I later post-processed to create the transparent layers, and worked on creating cohesive LUTs to match the overall tone. As a result, some expressed disappointment and disgust. So let's talk about it.

The concerns of anti-AI groups are significant and must not be overlooked. Fear, which is often justified, serves as a palpable common denominator. While technology is involved, my opinion is that our main concern should be on how companies could misuse it and exclude those most directly affected by decision-making processes.

Throughout history, concerns about technological disruption have been recurring themes, as I can attest from personal experience. Every innovation wave, from typewriters to microcomputers to the shift from analog to digital photography, caused worries about job security and creative control. Astonishingly, even the concept of “Control+Z” (undo) in digital art once drew criticism, with some artists lamenting, “Now you can’t own your mistakes.” Yet, despite initial misgivings and hurdles, these technological advancements have ultimately democratized creative tools, facilitating the widespread adoption of digital photography and design, among other fields.

The history of technology’s disruptive impact is paralleled by its evolution into a democratizing force. Take, for instance, the personal computer: a once-tremendous disruptor that now resides in our pockets, bags, and homes. These devices have empowered modern-day professionals to participate in a global economy and transformed the way we conduct business, pursue education, access entertainment, and communicate with one another.

Labor resistance to technological change has often culminated in defeat. An illustrative example brought up in this NYT article unfolded in 1986 when Rupert Murdoch relocated newspaper production from Fleet Street to a modern facility, leading to the abrupt dismissal of 6,000 workers. Instead of negotiating a gradual transition with worker support, the union’s absolute resistance to the technological change resulted in a loss with no compensation, underscoring the importance of strategic adaptation.

Surprisingly, the Writers Guild of America (W.G.A.) took a different approach when confronted with AI tools like ChatGPT. Rather than seeking an outright ban, they aimed to ensure that if AI was used to enhance writers’ productivity or quality, then guild members would receive a fair share of the benefits. Their efforts bore fruit, providing a promising model for other professional associations.

The crucial insight from these historical instances is that a thorough understanding of technology and strategic action can empower professionals to shape their future. In the current context, addressing AI-related concerns necessitates embracing knowledge, dispelling unwarranted fears, and arriving at negotiation tables equipped with informed decisions.

It's essential to develop and use AI in a responsible and ethical manner; developing safeguards against potential harm is necessary. It is important to have open and transparent conversations about the potential benefits and risks of AI.

Involving workers and other stakeholders in the decision-making process around AI development and deployment is a way to do this. The goal is to make sure AI benefits everyone and not just a chosen few.

While advocates for an outright ban on AI may have the best interests of fellow creatives in mind, unity and informed collaboration among those affected hold the key to ensuring a meaningful future where professionals are fairly compensated for their work. By excluding themselves from the discussion and ostracizing others who share most of their values and goals, they end up weakening chances of meaningful change; we need to understand the technology, its possibilities, and how it can be steered toward benefitting those they source from. And that involves practical experimentation, too. Carl Sagan, in his book 'The Demon-Haunted World: Science as a Candle in the Dark', said:

"I have a foreboding […] when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what's true, we slide, almost without noticing, back into superstition and darkness."

In a more personal tone, I'm proud to be married to a wonderful woman - an artist who has her physical artwork in all 50 US states, and several pieces sold around the world. For the last few years she has been studying and adapting her knowledge from analog to digital art, a fact that deeply inspired me to translate real photography practices to the virtual world of Eorzea. In the last months, she has been digging deep into generative AI in order to understand not only how it'll impact her professional life, but also how it can merge with her knowledge so it can enrich and benefit her art; this effort gives her the necessary clarity to voice her concerns, make her own choices and set her own agenda. I wish more people could see how useful her willingness and courage to dive into new technologies in order to understand their impact could be to help shape their own futures.

By comprehending AI and adopting a collective approach, we can transform the current challenges into opportunities. The democratization and responsible utilization of AI can herald a brighter future, where technology becomes a tool for empowerment and unity prevails over division. And now, let's go back to posting about pretty things.

[mariacallous]

The Biden administration’s approach to the governance of artificial intelligence (AI) began with the Blueprint for an AI Bill of Rights, released in October 2022. This framework highlighted five key principles to guide responsible AI development, including protections against algorithmic bias, privacy considerations, and the right to human oversight.

These early efforts set the tone for more extensive action, leading to the release of the Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, or the White House EO on AI, on October 30, 2023. This EO marked a critical step in defining AI regulation and accountability across multiple sectors, emphasizing a “whole-of-government” approach to address both opportunities and risks associated with AI. Last week, it reached its one-year anniversary.  

The 2023 Executive Order on Artificial Intelligence represents one of the U.S. government’s most comprehensive efforts to secure the development and application of AI technology. This EO set ambitious goals aimed at establishing the U.S. as a leader in safe, ethical, and responsible AI use. Specifically, the EO directed federal agencies to address several core areas: managing dual-use AI models, implementing rigorous testing protocols for high-risk AI systems, enforcing accountability measures, safeguarding civil rights, and promoting transparency across the AI lifecycle. These initiatives are designed to mitigate potential security risks and uphold democratic values while fostering public trust in the rapidly advancing field of AI.  

To recognize the one-year anniversary of the EO, the White House released a scorecard of achievements, pointing to the elevated work of various federal agencies, the voluntary agreements made with industry stakeholders, and the persistent efforts made to ensure that AI benefits the global talent market, accrues environmental benefits, and protects—not scrutinizes or dislocates—American workers.

One example is the work of the U.S. AI Safety Institute (AISI), housed in the National Institute of Standards and Technology (NIST), which has spearheaded pre-deployment testing of advanced AI models, working alongside private developers to strengthen AI safety science. The AISI has also signed agreements with leading AI companies to conduct red-team testing to identify and mitigate risks, especially for general-purpose models with potential national security implications.

In addition, NIST released Version 1.0 of its AI Risk Management Framework, which provides comprehensive guidelines for identifying, assessing, and mitigating risks across generative AI and dual-use models. This framework emphasizes core principles like safety, transparency, and accountability, establishing foundational practices for AI systems’ development and deployment. And just last week, the federal government released the first-ever National Security Memorandum on Artificial Intelligence, which will serve as the foundation for the U.S.’s safety and security efforts when it comes to AI. 

The White House EO on AI marks an essential step in shaping the future of U.S. AI policy, but its path forward remains uncertain with the pending presidential election. Since much of the work is being done by and within federal agencies, its tenets may outlive any possible repeal of the EO itself, ensuring the U.S. stays relevant in the development of guidance that balances the promotion of innovation with safety, particularly in national security. However, the EO’s long-term impact will depend on the willingness of policymakers to adapt to AI’s rapid development, while maintaining a framework that supports both innovation and public trust. Regardless of who leads the next administration, navigating these challenges will be central to cementing the U.S.’s role in the AI landscape on the global stage. 

In 2023, Brookings scholars weighed in following the adoption of the White House EO. Here’s what they have to say today around the one-year anniversary.

[creative-anchorage]

Meta AI will respond to a post in a group if someone explicitly tags it or if someone “asks a question in a post and no one responds within an hour.” [...] Meta AI has also been integrated into search features on Facebook and Instagram, and users cannot turn it off. As a researcher who studies both online communities and AI ethics, I find the idea of uninvited chatbots answering questions in Facebook groups to be dystopian for a number of reasons, starting with the fact that online communities are for people. ... [The] “real people” aspect of online communities continues to be critical today. Imagine why you might pose a question to a Facebook group rather than a search engine: because you want an answer from someone with real, lived experience or you want the human response that your question might elicit – sympathy, outrage, commiseration – or both. Decades of research suggests that the human component of online communities is what makes them so valuable for both information-seeking and social support. For example, fathers who might otherwise feel uncomfortable asking for parenting advice have found a haven in private online spaces just for dads. LGBTQ+ youth often join online communities to safely find critical resources while reducing feelings of isolation. Mental health support forums provide young people with belonging and validation in addition to advice and social support. In addition to similar findings in my own lab related to LGBTQ+ participants in online communities, as well as Black Twitter, two more recent studies, not yet peer-reviewed, have emphasized the importance of the human aspects of information-seeking in online communities. One, led by PhD student Blakeley Payne, focuses on fat people’s experiences online. Many of our participants found a lifeline in access to an audience and community with similar experiences as they sought and shared information about topics such as navigating hostile healthcare systems, finding clothing and dealing with cultural biases and stereotypes. Another, led by Ph.D student Faye Kollig, found that people who share content online about their chronic illnesses are motivated by the sense of community that comes with shared experiences, as well as the humanizing aspects of connecting with others to both seek and provide support and information. ... This isn’t to suggest that chatbots aren’t useful for anything – they may even be quite useful in some online communities, in some contexts. The problem is that in the midst of the current generative AI rush, there is a tendency to think that chatbots can and should do everything. ... Responsible AI development and deployment means not only auditing for issues such as bias and misinformation, but also taking the time to understand in which contexts AI is appropriate and desirable for the humans who will be interacting with them. Right now, many companies are wielding generative AI as a hammer, and as a result, everything looks like a nail. Many contexts, such as online support communities, are best left to humans.

[silicon-media-network]

Why AI Needs Us More Than We Need AI

In the modern era, artificial intelligence (AI) has become a transformative force, reshaping industries, enhancing efficiencies, and creating groundbreaking opportunities. However, amidst the excitement, it's essential to recognize that AI is not a standalone solution. Its existence and success hinge on human ingenuity, creativity, and ethical oversight.

The Human Role in AI Development

AI systems, no matter how advanced, are the products of human effort. From initial conceptualization to algorithm development, humans are the architects of AI. These systems rely on human-curated data to learn and evolve. Without accurate, diverse, and unbiased data provided by humans, AI models risk being ineffective or perpetuating societal biases.

Furthermore, human expertise is critical in defining the objectives and boundaries of AI applications. For instance, an AI used in healthcare must be tailored to specific medical scenarios, a process that requires domain knowledge from professionals in the field. This collaboration between AI and human experts ensures that the technology addresses real-world challenges effectively.

Ethical Oversight and Accountability

One of the most vital aspects where humans play a pivotal role is in ethical decision-making. AI lacks the moral compass to discern right from wrong. Decisions involving fairness, privacy, and societal impact must be guided by human values. Without this oversight, AI could exacerbate inequalities or infringe on individual rights.

Regulatory frameworks and ethical guidelines developed by humans act as guardrails for AI deployment. These frameworks ensure that AI is used responsibly and aligns with societal norms. For example, determining the boundaries of facial recognition technology in public spaces is a human-driven decision, balancing security needs with privacy concerns.

Innovation Through Collaboration

While AI can process vast amounts of information faster than humans, it cannot replicate human creativity and emotional intelligence. Many innovations stem from human intuition, curiosity, and the ability to think abstractly. By working alongside AI, humans can leverage the technology’s strengths while providing the imaginative spark that drives true innovation.

Fields like art, design, and storytelling highlight this synergy. AI can generate ideas or assist in tasks, but the essence of creativity remains uniquely human. This collaborative dynamic fosters groundbreaking advancements that neither humans nor AI could achieve alone.

Why AI Depends on Us

At its core, AI is a tool. It requires human input to function and evolve. The algorithms, hardware, and infrastructure that power AI are all designed and maintained by humans. Moreover, the continuous improvement of AI systems depends on ongoing research and experimentation—activities driven by human intellect.

AI also lacks the capacity for independent thought, emotional understanding, and context awareness. These are fundamental human traits that guide nuanced decision-making and problem-solving. Without these qualities, AI would be limited to executing predefined tasks, incapable of adapting to complex, dynamic environments.

The Human-AI Partnership

Rather than viewing AI as a replacement for human effort, it should be seen as a partner that amplifies our abilities. This partnership can unlock unparalleled opportunities, but it’s humans who will steer the course. By setting goals, providing context, and ensuring ethical practices, we remain the driving force behind AI’s impact on society.

Conclusion

While AI holds immense potential, it ultimately depends on human expertise, creativity, and values to realize its promise. As we integrate AI into more aspects of our lives, it’s crucial to remember that this technology needs us more than we need it. By embracing our role as its creators and stewards, we can ensure that AI serves humanity responsibly and effectively.

Explore more about the symbiotic relationship between humans and AI at Why AI Needs Us More Than We Need AI.

[ktaminfo]

Keys to the Digital Future

The digital future is not merely a continuation of today’s technological trends; it is a transformative landscape where innovation, connectivity, and sustainability intertwine to redefine how we live, work, and interact. As we step into this exciting future, understanding its essential components can empower individuals, businesses, and societies to thrive. Here are the key elements shaping the digital future:

Artificial Intelligence (AI) and Machine Learning (ML)

AI and ML are at the forefront of the digital transformation. These technologies are driving advancements in automation, data analysis, and decision-making. From personalized recommendations to autonomous vehicles, AI’s capabilities are reshaping industries. The future lies in ethical AI development, ensuring these tools enhance human lives while minimizing biases and risks.

The Internet of Things (IoT)

The IoT connects devices, systems, and people, creating an ecosystem of interconnectivity. Smart homes, wearables, and industrial IoT solutions are just the beginning. As 5G and edge computing mature, IoT’s potential to streamline operations and improve efficiency will expand exponentially, transforming everything from healthcare to urban planning.

3. Sustainable Technologies

The digital future must align with global sustainability goals. Renewable energy, energy-efficient data centers, and green computing practices are essential for reducing the environmental footprint of technology. The circular economy, which emphasizes recycling and repurposing electronic waste, will play a significant role in creating a sustainable digital ecosystem.

Cybersecurity and Privacy

As technology evolves, so do the threats associated with it. Cybersecurity is a cornerstone of the digital future, requiring robust frameworks to protect data and infrastructure. Privacy-centric technologies, such as blockchain and zero-knowledge proofs, offer innovative ways to safeguard user data and build trust in digital systems.

Digital Inclusion and Accessibility

A truly transformative digital future is one that is inclusive and accessible to all. Bridging the digital divide requires investments in infrastructure, affordable devices, and digital literacy programs. Technologies must be designed with accessibility in mind, ensuring equitable opportunities for everyone, regardless of location, ability, or socioeconomic status.

Quantum Computing

Quantum computing has the potential to solve problems that are currently beyond the reach of classical computers. By leveraging quantum mechanics, these machines can revolutionize fields such as cryptography, drug discovery, and climate modeling. While still in its infancy, quantum computing is a critical component of the digital frontier.

The Metaverse and Virtual Realities

The metaverse represents the convergence of physical and digital realities. Virtual and augmented reality technologies are enabling new ways of interaction, education, and entertainment. Businesses are leveraging these immersive environments for training, product design, and customer engagement, laying the foundation for a blended digital-physical world.

Ethical Leadership in Technology

The digital future demands leaders who prioritize ethics and societal well-being. From addressing algorithmic biases to ensuring responsible AI deployment, ethical leadership is crucial for fostering innovation that aligns with human values. Transparency, accountability, and collaboration will be key to navigating complex ethical challenges.

Education and Lifelong Learning

As technology evolves, so must our skills. The future workforce will require adaptability and continuous learning to keep pace with new tools and paradigms. Education systems must evolve to emphasize digital literacy, critical thinking, and collaboration, preparing individuals for the demands of a rapidly changing digital landscape.

Global Collaboration

The digital future is a global endeavor, requiring collaboration across borders, industries, and disciplines. Shared goals, such as mitigating climate change and advancing healthcare, necessitate partnerships that leverage collective expertise and resources. International cooperation will ensure that technological advancements benefit humanity as a whole.

The keys to the digital future lie in innovation, inclusivity, and sustainability. By embracing these principles and addressing the challenges they present, we can unlock unprecedented opportunities for growth and prosperity. As we navigate this dynamic journey, the digital future promises to be a realm of endless possibilities, limited only by our imagination and commitment to shaping it responsibly.

[jcmarchi]

The rise of multimodal AI: A fight against fraud

New Post has been published on https://thedigitalinsider.com/the-rise-of-multimodal-ai-a-fight-against-fraud/

The rise of multimodal AI: A fight against fraud

In the rapidly evolving world of artificial intelligence, a new frontier is emerging that promises both immense potential and significant risks – multimodal large language models (LLMs).

These advanced AI systems can process and generate different data types like text, images, audio, and video, enabling a wide range of applications from creative content generation to enhanced virtual assistants.

However, as with any transformative technology, there is a darker side that must be addressed – the potential for misuse by bad actors, including fraudsters.

One of the most concerning aspects of multimodal LLMs is their ability to generate highly realistic synthetic media, commonly known as deepfakes. These AI-generated videos, audio, or images can be virtually indistinguishable from the real thing, opening up a Pandora’s box of potential misuse.

Fraudsters could leverage deepfakes to impersonate individuals for purposes like financial fraud, identity theft, or even extortion through non-consensual intimate imagery.

Moreover, the scale and personalization capabilities of LLMs raise the specter of deepfake-powered social engineering attacks on an unprecedented level. Bad actors could potentially generate tailored multimedia content at scale, crafting highly convincing phishing scams or other fraudulent schemes designed to exploit human vulnerabilities.

Poisoning the well: Synthetic data risks

Another area of concern lies in the potential for fraudsters to inject malicious synthetic data into the training sets used to build LLM models. By carefully crafting and injecting multi-modal data (text, images, audio, etc.), bad actors could attempt to “poison” the model, causing it to learn and amplify undesirable behaviors or biases that enable downstream abuse.

This risk is particularly acute in scenarios where LLM models are deployed in critical decision-making contexts, such as financial services, healthcare, or legal domains. A compromised model could potentially make biased or erroneous decisions, leading to significant harm or enabling fraudulent activities.

Evading moderation and amplifying biases

Even without intentional “poisoning,” there is a risk that LLM models may inadvertently learn and propagate unethical biases or generate potentially abusive content that evades existing moderation filters. This is due to the inherent challenges of curating and filtering the massive, diverse datasets used to train these models.

For instance, an LLM trained on certain internet data could potentially pick up and amplify societal biases around race, gender, or other protected characteristics, leading to discriminatory outputs. Similarly, an LLM trained on unfiltered online content could conceivably generate hate speech, misinformation, or other harmful content if not properly governed.

Responsible AI: A necessity, not a choice

While the potential risks of multimodal LLMs are significant, it is crucial to recognize that these technologies also hold immense potential for positive impact across various domains. From enhancing accessibility through multimedia content generation to enabling more natural and intuitive human-machine interactions, the benefits are vast and far-reaching.

However, realizing this potential while mitigating the risks requires a proactive and steadfast commitment to responsible AI development and governance. This involves a multifaceted approach spanning various strategies.

1. Robust data vetting and curation

Implementing rigorous processes to vet the provenance, quality, and integrity of training data before feeding it into LLM models. This includes advanced techniques for detecting and filtering out synthetic or manipulated data.

2. Digital watermarking and traceability

Embedding robust digital watermarks or signatures in generated media to enable traceability and detection of synthetic content. This could aid in identifying deepfakes and holding bad actors accountable.

3. Human-AI collaboration and controlled sandboxing

Ensuring that LLM-based content generation is not a fully autonomous process but rather involves meaningful human oversight, clear guidelines, and controlled “sandboxing” environments to mitigate potential misuse.

4. Comprehensive model risk assessment

Conducting thorough risk modeling, testing, and auditing of LLM models pre-deployment to identify potential failure modes, vulnerabilities, or unintended behaviors that could enable fraud or abuse.

5. Continuous monitoring and adaptation

Implementing robust monitoring systems to continuously track the performance and outputs of deployed LLM models, enabling timely adaptation and mitigation strategies in response to emerging threats or misuse patterns.

6. Cross-stakeholder collaboration

Fostering collaboration and knowledge-sharing among AI developers, researchers, policymakers, and industry stakeholders to collectively advance best practices, governance frameworks, and technological solutions for responsible AI.

The path forward is clear – the incredible potential of multimodal LLMs must be balanced with a steadfast commitment to ethics, security, and responsible innovation. By proactively addressing the risks and implementing robust governance measures, we can harness the power of these technologies to drive progress while safeguarding against their misuse by fraudsters and bad actors.

In the eternal race between those seeking to exploit technology for nefarious ends and those working to secure and protect it, the emergence of multimodal LLMs represents a new battlefront.

It is a fight we cannot afford to lose, as the stakes – from financial security to the integrity of information itself – are simply too high. With vigilance, collaboration, and an unwavering ethical compass, we can navigate this new frontier and ensure that the immense potential of multimodal AI is a force for good, not a paradise for fraudsters.

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AI Accelerator Institute Pro+ membership

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[itcareerblogs]

Top 10 In- Demand Tech Jobs in 2025

Technology is growing faster than ever, and so is the need for skilled professionals in the field. From artificial intelligence to cloud computing, businesses are looking for experts who can keep up with the latest advancements. These tech jobs not only pay well but also offer great career growth and exciting challenges.

In this blog, we’ll look at the top 10 tech jobs that are in high demand today. Whether you’re starting your career or thinking of learning new skills, these jobs can help you plan a bright future in the tech world.

1. AI and Machine Learning Specialists

Artificial Intelligence (AI)  and Machine Learning are changing the game by helping machines learn and improve on their own without needing step-by-step instructions. They’re being used in many areas, like chatbots, spotting fraud, and predicting trends.

Key Skills: Python, TensorFlow, PyTorch, data analysis, deep learning, and natural language processing (NLP).

Industries Hiring: Healthcare, finance, retail, and manufacturing.

Career Tip: Keep up with AI and machine learning by working on projects and getting an AI certification. Joining AI hackathons helps you learn and meet others in the field.

2. Data Scientists

Data scientists work with large sets of data to find patterns, trends, and useful insights that help businesses make smart decisions. They play a key role in everything from personalized marketing to predicting health outcomes.

Key Skills: Data visualization, statistical analysis, R, Python, SQL, and data mining.

Industries Hiring: E-commerce, telecommunications, and pharmaceuticals.

Career Tip: Work with real-world data and build a strong portfolio to showcase your skills. Earning certifications in data science tools can help you stand out.

3. Cloud Computing Engineers: These professionals create and manage cloud systems that allow businesses to store data and run apps without needing physical servers, making operations more efficient.

Key Skills: AWS, Azure, Google Cloud Platform (GCP), DevOps, and containerization (Docker, Kubernetes).

Industries Hiring: IT services, startups, and enterprises undergoing digital transformation.

Career Tip: Get certified in cloud platforms like AWS (e.g., AWS Certified Solutions Architect).

4. Cybersecurity Experts

Cybersecurity professionals protect companies from data breaches, malware, and other online threats. As remote work grows, keeping digital information safe is more crucial than ever.

Key Skills: Ethical hacking, penetration testing, risk management, and cybersecurity tools.

Industries Hiring: Banking, IT, and government agencies.

Career Tip: Stay updated on new cybersecurity threats and trends. Certifications like CEH (Certified Ethical Hacker) or CISSP (Certified Information Systems Security Professional) can help you advance in your career.

5. Full-Stack Developers

Full-stack developers are skilled programmers who can work on both the front-end (what users see) and the back-end (server and database) of web applications.

Key Skills: JavaScript, React, Node.js, HTML/CSS, and APIs.

Industries Hiring: Tech startups, e-commerce, and digital media.

Career Tip: Create a strong GitHub profile with projects that highlight your full-stack skills. Learn popular frameworks like React Native to expand into mobile app development.

6. DevOps Engineers

DevOps engineers help make software faster and more reliable by connecting development and operations teams. They streamline the process for quicker deployments.

Key Skills: CI/CD pipelines, automation tools, scripting, and system administration.

Industries Hiring: SaaS companies, cloud service providers, and enterprise IT.

Career Tip: Earn key tools like Jenkins, Ansible, and Kubernetes, and develop scripting skills in languages like Bash or Python. Earning a DevOps certification is a plus and can enhance your expertise in the field.

7. Blockchain Developers

They build secure, transparent, and unchangeable systems. Blockchain is not just for cryptocurrencies; it’s also used in tracking supply chains, managing healthcare records, and even in voting systems.

Key Skills: Solidity, Ethereum, smart contracts, cryptography, and DApp development.

Industries Hiring: Fintech, logistics, and healthcare.

Career Tip: Create and share your own blockchain projects to show your skills. Joining blockchain communities can help you learn more and connect with others in the field.

8. Robotics Engineers

Robotics engineers design, build, and program robots to do tasks faster or safer than humans. Their work is especially important in industries like manufacturing and healthcare.

Key Skills: Programming (C++, Python), robotics process automation (RPA), and mechanical engineering.

Industries Hiring: Automotive, healthcare, and logistics.

Career Tip: Stay updated on new trends like self-driving cars and AI in robotics.

9. Internet of Things (IoT) Specialists

IoT specialists work on systems that connect devices to the internet, allowing them to communicate and be controlled easily. This is crucial for creating smart cities, homes, and industries.

Key Skills: Embedded systems, wireless communication protocols, data analytics, and IoT platforms.

Industries Hiring: Consumer electronics, automotive, and smart city projects.

Career Tip: Create IoT prototypes and learn to use platforms like AWS IoT or Microsoft Azure IoT. Stay updated on 5G technology and edge computing trends.

10. Product Managers

Product managers oversee the development of products, from idea to launch, making sure they are both technically possible and meet market demands. They connect technical teams with business stakeholders.

Key Skills: Agile methodologies, market research, UX design, and project management.

Industries Hiring: Software development, e-commerce, and SaaS companies.

Career Tip: Work on improving your communication and leadership skills. Getting certifications like PMP (Project Management Professional) or CSPO (Certified Scrum Product Owner) can help you advance.

Importance of Upskilling in the Tech Industry

Stay Up-to-Date: Technology changes fast, and learning new skills helps you keep up with the latest trends and tools.

Grow in Your Career: By learning new skills, you open doors to better job opportunities and promotions.

Earn a Higher Salary: The more skills you have, the more valuable you are to employers, which can lead to higher-paying jobs.

Feel More Confident: Learning new things makes you feel more prepared and ready to take on tougher tasks.

Adapt to Changes: Technology keeps evolving, and upskilling helps you stay flexible and ready for any new changes in the industry.

Top Companies Hiring for These Roles

Global Tech Giants: Google, Microsoft, Amazon, and IBM.

Startups: Fintech, health tech, and AI-based startups are often at the forefront of innovation.

Consulting Firms: Companies like Accenture, Deloitte, and PwC increasingly seek tech talent.

In conclusion,  the tech world is constantly changing, and staying updated is key to having a successful career. In 2025, jobs in fields like AI, cybersecurity, data science, and software development will be in high demand. By learning the right skills and keeping up with new trends, you can prepare yourself for these exciting roles. Whether you're just starting or looking to improve your skills, the tech industry offers many opportunities for growth and success.