In an interview ahead of the AI & Big Data Expo North America, Igor Jablokov, CEO and founder of AI company Pryon, addressed these pressing issues head-on.

Critical ethical challenges in AI

“There’s not one, maybe there’s almost 20 plus of them,” Jablokov stated when asked about the most critical ethical challenges. He outlined a litany of potential pitfalls that must be carefully navigated—from AI hallucinations and emissions of falsehoods, to data privacy violations and intellectual property leaks from training on proprietary information.

Bias and adversarial content seeping into training data is another major worry, according to Jablokov. Security vulnerabilities like embedded agents and prompt injection attacks also rank highly on his list of concerns, as well as the extreme energy consumption and climate impact of large language models.

Pryon’s origins can be traced back to the earliest stirrings of modern AI over two decades ago. Jablokov previously led an advanced AI team at IBM where they designed a primitive version of what would later become Watson. “They didn’t greenlight it. And so, in my frustration, I departed, stood up our last company,” he recounted. That company, also called Pryon at the time, went on to become Amazon’s first AI-related acquisition, birthing what’s now Alexa.

The current incarnation of Pryon has aimed to confront AI’s ethical quandaries through responsible design focused on critical infrastructure and high-stakes use cases. “[We wanted to] create something purposely hardened for more critical infrastructure, essential workers, and more serious pursuits,” Jablokov explained.

A key element is offering enterprises flexibility and control over their data environments. “We give them choices in terms of how they’re consuming their platforms…from multi-tenant public cloud, to private cloud, to on-premises,” Jablokov said. This allows organisations to ring-fence highly sensitive data behind their own firewalls when needed.

Pryon also emphasises explainable AI and verifiable attribution of knowledge sources. “When our platform reveals an answer, you can tap it, and it always goes to the underlying page and highlights exactly where it learned a piece of information from,” Jablokov described. This allows human validation of the knowledge provenance.

In some realms like energy, manufacturing, and healthcare, Pryon has implemented human-in-the-loop oversight before AI-generated guidance goes to frontline workers. Jablokov pointed to one example where “supervisors can double-check the outcomes and essentially give it a badge of approval” before information reaches technicians.

Ensuring responsible AI development

Jablokov strongly advocates for new regulatory frameworks to ensure responsible AI development and deployment. While welcoming the White House’s recent executive order as a start, he expressed concerns about risks around generative AI like hallucinations, static training data, data leakage vulnerabilities, lack of access controls, copyright issues, and more.  

Pryon has been actively involved in these regulatory discussions. “We’re back-channelling to a mess of government agencies,” Jablokov said. “We’re taking an active hand in terms of contributing our perspectives on the regulatory environment as it rolls out…We’re showing up by expressing some of the risks associated with generative AI usage.”

On the potential for an uncontrolled, existential “AI risk” – as has been warned about by some AI leaders – Jablokov struck a relatively sanguine tone about Pryon’s governed approach: “We’ve always worked towards verifiable attribution…extracting out of enterprises’ own content so that they understand where the solutions are coming from, and then they decide whether they make a decision with it or not.”

The CEO firmly distanced Pryon’s mission from the emerging crop of open-ended conversational AI assistants, some of which have raised controversy around hallucinations and lacking ethical constraints.

“We’re not a clown college. Our stuff is designed to go into some of the more serious environments on planet Earth,” Jablokov stated bluntly. “I think none of you would feel comfortable ending up in an emergency room and having the medical practitioners there typing in queries into a ChatGPT, a Bing, a Bard…”

He emphasised the importance of subject matter expertise and emotional intelligence when it comes to high-stakes, real-world decision-making. “You want somebody that has hopefully many years of experience treating things similar to the ailment that you’re currently undergoing. And guess what? You like the fact that there is an emotional quality that they care about getting you better as well.”

At the upcoming AI & Big Data Expo, Pryon will unveil new enterprise use cases showcasing its platform across industries like energy, semiconductors, pharmaceuticals, and government. Jablokov teased that they will also reveal “different ways to consume the Pryon platform” beyond the end-to-end enterprise offering, including potentially lower-level access for developers.

As AI’s domain rapidly expands from narrow applications to more general capabilities, addressing the ethical risks will become only more critical. Pryon’s sustained focus on governance, verifiable knowledge sources, human oversight, and collaboration with regulators could offer a template for more responsible AI development across industries.

You can watch our full interview with Igor Jablokov below:

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 BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post Igor Jablokov, Pryon: Building a responsible AI future appeared first on AI News.

This is according to a study conducted in early 2024 by Coleman Parkes Research and sponsored by data analytics firm SAS, which surveyed 300 US GenAI strategy or data analytics decision makers to pulse check major areas of investment and the hurdles organisations are facing.

Marinela Profi, strategic AI advisor at SAS, said: “Organisations are realising that large language models (LLMs) alone don’t solve business challenges. 

“GenAI should be treated as an ideal contributor to hyper automation and the acceleration of existing processes and systems rather than the new shiny toy that will help organisations realise all their business aspirations. Time spent developing a progressive strategy and investing in technology that offers integration, governance and explainability of LLMs are crucial steps all organisations should take before jumping in with both feet and getting ‘locked in.’”

Organisations are hitting stumbling blocks in four key areas of implementation:

• Increasing trust in data usage and achieving compliance. Only one in 10 organisations has a reliable system in place to measure bias and privacy risk in LLMs. Moreover, 93% of U.S. businesses lack a comprehensive governance framework for GenAI, and the majority are at risk of noncompliance when it comes to regulation.

• Integrating GenAI into existing systems and processes. Organisations reveal they’re experiencing compatibility issues when trying to combine GenAI with their current systems.

• Talent and skills. In-house GenAI is lacking. As HR departments encounter a scarcity of suitable hires, organisational leaders worry they don’t have access to the necessary skills to make the most of their GenAI investment.

• Predicting costs. Leaders cite prohibitive direct and indirect costs associated with using LLMs. Model creators provide a token cost estimate (which organisations now realise is prohibitive). But the costs for private knowledge preparation, training and ModelOps management are lengthy and complex.

Profi added: “It’s going to come down to identifying real-world use cases that deliver the highest value and solve human needs in a sustainable and scalable manner. 

“Through this study, we’re continuing our commitment to helping organisations stay relevant, invest their money wisely and remain resilient. In an era where AI technology evolves almost daily, competitive advantage is highly dependent on the ability to embrace the resiliency rules.”

Details of the study were unveiled today at SAS Innovate in Las Vegas, SAS Software’s AI and analytics conference for business leaders, technical users and SAS partners.

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 BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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

The post 80% of AI decision makers are worried about data privacy and security appeared first on AI News.

Generative AI tools have enabled cybercriminals to craft convincing scams, including voice cloning to impersonate family members seeking money or manipulating authentic videos with “cheapfakes.” These tactics manipulate content to deceive individuals, creating a heightened challenge for consumers to discern between real and manipulated information.

In response to this challenge, McAfee Labs developed an industry-leading AI model, part of the Project Mockingbird technology, to detect AI-generated audio. This technology employs contextual, behavioural, and categorical detection models, achieving an impressive 90 percent accuracy rate.

Steve Grobman, CTO at McAfee, said: “Much like a weather forecast indicating a 70 percent chance of rain helps you plan your day, our technology equips you with insights to make educated decisions about whether content is what it appears to be.”

Project Mockingbird offers diverse applications, from countering AI-generated scams to tackling disinformation. By empowering consumers to distinguish between authentic and manipulated content, McAfee aims to protect users from falling victim to fraudulent schemes and ensure a secure digital experience.

Deep concerns about deepfakes

As deepfake technology becomes more sophisticated, consumer concerns are on the rise. McAfee’s December 2023 Deepfakes Survey highlights:

• 84% of Americans are concerned about deepfake usage in 2024
• 68% are more concerned than a year ago
• 33% have experienced or witnessed a deepfake scam, with 40% prevalent among 18–34 year-olds
• Top concerns include election influence (52%), undermining public trust in media (48%), impersonation of public figures (49%), proliferation of scams (57%), cyberbullying (44%), and sexually explicit content creation (37%)

McAfee’s unveiling of Project Mockingbird marks a significant leap in the ongoing battle against AI-generated threats. As countries like the US and UK enter a pivotal election year, it’s crucial that consumers are given the best chance possible at grappling with the pervasive influence of deepfake technology.

(Photo by Markus Spiske on Unsplash)

See also: MyShell releases OpenVoice voice cloning AI

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 Digital Transformation Week and Cyber Security & Cloud Expo.

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

The post McAfee unveils AI-powered deepfake audio detection appeared first on AI News.

The guidelines were developed by the UK’s National Cyber Security Centre (NCSC) and the US’ Cybersecurity and Infrastructure Security Agency (CISA). They have already secured endorsements from 17 other countries, including all G7 members.

The guidelines provide recommendations for developers and organisations using AI to incorporate cybersecurity at every stage. This “secure by design” approach advises baking in security from the initial design phase through development, deployment, and ongoing operations.  

Specific guidelines cover four key areas: secure design, secure development, secure deployment, and secure operation and maintenance. They suggest security behaviours and best practices for each phase.

The launch event in London convened over 100 industry, government, and international partners. Speakers included reps from Microsoft, the Alan Turing Institute, and cyber agencies from the US, Canada, Germany, and the UK.  

NCSC CEO Lindy Cameron stressed the need for proactive security amidst AI’s rapid pace of development. She said, “security is not a postscript to development but a core requirement throughout.”

The guidelines build on existing UK leadership in AI safety. Last month, the UK hosted the first international summit on AI safety at Bletchley Park.

US Secretary of Homeland Security Alejandro Mayorkas said: “We are at an inflection point in the development of artificial intelligence, which may well be the most consequential technology of our time. Cybersecurity is key to building AI systems that are safe, secure, and trustworthy.

“The guidelines jointly issued today by CISA, NCSC, and our other international partners, provide a common-sense path to designing, developing, deploying, and operating AI with cybersecurity at its core.”

The 18 endorsing countries span Europe, Asia-Pacific, Africa, and the Americas. Here is the full list of international signatories:

• Australia – Australian Signals Directorate’s Australian Cyber Security Centre (ACSC)
• Canada – Canadian Centre for Cyber Security (CCCS) 
• Chile – Chile’s Government CSIRT
• Czechia – Czechia’s National Cyber and Information Security Agency (NUKIB)
• Estonia – Information System Authority of Estonia (RIA) and National Cyber Security Centre of Estonia (NCSC-EE)
• France – French Cybersecurity Agency (ANSSI)
• Germany – Germany’s Federal Office for Information Security (BSI)
• Israel – Israeli National Cyber Directorate (INCD)
• Italy – Italian National Cybersecurity Agency (ACN)
• Japan – Japan’s National Center of Incident Readiness and Strategy for Cybersecurity (NISC; Japan’s Secretariat of Science, Technology and Innovation Policy, Cabinet Office
• New Zealand – New Zealand National Cyber Security Centre
• Nigeria – Nigeria’s National Information Technology Development Agency (NITDA)
• Norway – Norwegian National Cyber Security Centre (NCSC-NO)
• Poland – Poland’s NASK National Research Institute (NASK)
• Republic of Korea – Republic of Korea National Intelligence Service (NIS)
• Singapore – Cyber Security Agency of Singapore (CSA)
• United Kingdom – National Cyber Security Centre (NCSC)
• United States of America – Cybersecurity and Infrastructure Agency (CISA); National Security Agency (NSA; Federal Bureau of Investigations (FBI)

UK Science and Technology Secretary Michelle Donelan positioned the new guidelines as cementing the UK’s role as “an international standard bearer on the safe use of AI.”

“Just weeks after we brought world leaders together at Bletchley Park to reach the first international agreement on safe and responsible AI, we are once again uniting nations and companies in this truly global effort,” adds Donelan.

The guidelines are now published on the NCSC website alongside explanatory blogs. Developer uptake will be key to translating the secure by design vision into real-world improvements in AI security.

(Photo by Jan Antonin Kolar on Unsplash)

See also: Paul O’Sullivan, Salesforce: Transforming work in the GenAI era

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 Cyber Security & Cloud Expo and Digital Transformation Week.

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

The post Global AI security guidelines endorsed by 18 countries appeared first on AI News.

The recent GitLab 16.6 November release includes the beta launch of GitLab Duo Chat, a natural-language AI assistant. Additionally, the GitLab 16.7 December release sees the general availability of GitLab Duo Code Suggestions.

David DeSanto, Chief Product Officer at GitLab, said: “To realise AI’s full potential, it needs to be embedded across the software development lifecycle, allowing DevSecOps teams to benefit from boosts to security, efficiency, and collaboration.”

GitLab Duo Chat – arguably the star of the show – provides users with invaluable insights, guidance, and suggestions. Beyond code analysis, it supports planning, security issue comprehension and resolution, troubleshooting CI/CD pipeline failures, aiding in merge requests, and more.

As part of GitLab’s commitment to providing a comprehensive AI-powered experience, Duo Chat joins Code Suggestions as the primary interface into GitLab’s AI suite within its DevSecOps platform.

GitLab Duo comprises a suite of 14 AI capabilities:

• Suggested Reviewers
• Code Suggestions
• Chat
• Vulnerability Summary
• Code Explanation
• Planning Discussions Summary
• Merge Request Summary
• Merge Request Template Population
• Code Review Summary
• Test Generation
• Git Suggestions
• Root Cause Analysis
• Planning Description Generation
• Value Stream Forecasting

In response to the evolving needs of development, security, and operations teams, Code Suggestions is now generally available. This feature assists in creating and updating code, reducing cognitive load, enhancing efficiency, and accelerating secure software development.

GitLab’s commitment to privacy and transparency stands out in the AI space. According to the GitLab report, 83 percent of DevSecOps professionals consider implementing AI in their processes essential, with 95 percent prioritising privacy and intellectual property protection in AI tool selection.

The State of AI in Software Development report by GitLab reveals that developers spend just 25 percent of their time writing code. The Duo suite aims to address this by reducing toolchain sprawl—enabling 7x faster cycle times, heightened developer productivity, and reduced software spend.

Kate Holterhoff, Industry Analyst at Redmonk, commented: “The developers we speak with at RedMonk are keenly interested in the productivity and efficiency gains that code assistants promise.

“GitLab’s Duo Code Suggestions is a welcome player in this space, expanding the available options for enabling an AI-enhanced software development lifecycle.”

(Photo by Pankaj Patel on Unsplash)

See also: OpenAI battles DDoS against its API and ChatGPT services

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 Cyber Security & Cloud Expo and Digital Transformation Week.

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

The post GitLab’s new AI capabilities empower DevSecOps appeared first on AI News.

While the company has not yet disclosed specific details about the source of these attacks, OpenAI acknowledged that they are dealing with “periodic outages due to an abnormal traffic pattern reflective of a DDoS attack.”

Users affected by these incidents reported encountering errors such as “something seems to have gone wrong” and “There was an error generating a response” when accessing ChatGPT.

This recent wave of attacks follows a major outage that impacted ChatGPT and its API on Wednesday, along with partial ChatGPT outages on Tuesday, and elevated error rates in Dall-E on Monday.

OpenAI displayed a banner across ChatGPT’s interface, attributing the disruptions to “exceptionally high demand” and reassuring users that efforts were underway to scale their systems.

Threat actor group Anonymous Sudan has claimed responsibility for the DDoS attacks on OpenAI. According to the group, the attacks are in response to OpenAI’s perceived bias towards Israel and against Palestine.

The attackers utilised the SkyNet botnet, which recently incorporated support for application layer attacks or Layer 7 (L7) DDoS attacks. In Layer 7 attacks, threat actors overwhelm services at the application level with a massive volume of requests to strain the targets’ server and network resources.

Brad Freeman, Director of Technology at SenseOn, commented:

“Distributed denial of service attacks are internet vandalism. Low effort, complexity, and in most cases more of a nuisance than a long-term threat to a business. Often DDOS attacks target services with high volumes of traffic which can be ’off-ramped, by their cloud or Internet service provider.

However, as the attacks are on Layer 7 they will be targeting the application itself, therefore OpenAI will need to make some changes to mitigate the attack. It’s likely the threat actor is sending complex queries to OpenAI to overload it, I wonder if they are using AI-generated content to attack AI content generation.”

However, the attribution of these attacks to Anonymous Sudan has raised suspicions among cybersecurity researchers. Some experts suggest that this could be a false flag operation and the group might have connections to Russia instead which, along with Iran, is suspected of stoking the bloodshed and international outrage to benefit its domestic interests.

The situation once again highlights the ongoing challenges faced by organisations dealing with DDoS attacks and the complexities of accurately identifying the perpetrators.

(Photo by Johann Walter Bantz on Unsplash)

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 Cyber Security & Cloud Expo.

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

The post OpenAI battles DDoS against its API and ChatGPT services appeared first on AI News.

This development was announced in a document published to the Federal Registry on November 2, alongside an official notice inviting applications from individuals with the relevant credentials.

The document states, “This notice is the initial step for NIST in collaborating with non-profit organisations, universities, other government agencies, and technology companies to address challenges associated with the development and deployment of AI.”

The primary objective of this collaboration is to create and implement specific policies and measurements that ensure a human-centred approach to AI safety and governance within the United States.

Collaborators within the consortium will be tasked with a range of functions, including the development of measurement and benchmarking tools, policy recommendations, red-teaming efforts, psychoanalysis, and environmental analysis.

NIST’s initiative comes in response to a recent executive order issued by US President Joseph Biden, which outlined six new standards for AI safety and security.

While European and Asian countries have been proactive in instituting policies governing AI systems concerning user and citizen privacy, security, and potential unintended consequences, the US has lagged.

President Biden’s executive order and the establishment of the Safety Institute Consortium mark significant strides in the right direction, yet there remains a lack of clarity regarding the timeline for the implementation of laws governing AI development and deployment in the US.

Many experts have expressed concerns about the adequacy of current laws, designed for conventional businesses and technology, when applied to the rapidly-evolving AI sector.

The formation of the AI consortium signifies a crucial step towards shaping the future of AI policies in the US. It reflects a collaborative effort between government bodies, non-profit organisations, universities, and technology companies to ensure responsible and ethical AI practices within the nation.

(Photo by Muhammad Rizki on Unsplash)

See also: UK paper highlights AI risks ahead of global Safety Summit

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 Digital Transformation Week.

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

The post NIST announces AI consortium to shape US policies appeared first on AI News.

The order establishes stringent standards for AI safety and security, safeguards Americans’ privacy, promotes equity and civil rights, protects consumers and workers, fosters innovation and competition, and enhances American leadership on the global stage.

Key actions outlined in the order:

1. New standards for AI safety and security: The order mandates that developers of powerful AI systems share safety test results and critical information with the U.S. government. Rigorous standards, tools, and tests will be developed to ensure AI systems are safe, secure, and trustworthy before public release. Additionally, measures will be taken to protect against the risks of using AI to engineer dangerous biological materials and combat AI-enabled fraud and deception.
2. Protecting citizens’ privacy: The President calls on Congress to pass bipartisan data privacy legislation, prioritizing federal support for privacy-preserving techniques, especially those using AI. Guidelines will be developed for federal agencies to evaluate the effectiveness of privacy-preserving techniques, including those used in AI systems.
3. Advancing equity and civil rights: Clear guidance will be provided to prevent AI algorithms from exacerbating discrimination, especially in areas like housing and federal benefit programs. Best practices will be established for the use of AI in the criminal justice system to ensure fairness.
4. Standing up for consumers, patients, and students: Responsible use of AI in healthcare and education will be promoted, ensuring that consumers are protected from harmful AI applications while benefiting from its advancements in these sectors.
5. Supporting workers: Principles and best practices will be developed to mitigate the harms and maximise the benefits of AI for workers, addressing issues such as job displacement, workplace equity, and health and safety. A report on AI’s potential labour-market impacts will be produced, identifying options for strengthening federal support for workers facing labour disruptions due to AI.
6. Promoting innovation and competition: The order aims to catalyse AI research across the US, promote a fair and competitive AI ecosystem, and expand the ability of highly skilled immigrants and non-immigrants to study, stay, and work in the US to foster innovation in the field.
7. Advancing leadership abroad: The US will collaborate with other nations to establish international frameworks for safe and trustworthy AI deployment. Efforts will be made to accelerate the development and implementation of vital AI standards with international partners and promote the responsible development and deployment of AI abroad to address global challenges.
8. Ensuring responsible and effective government adoption: Clear standards and guidelines will be issued for government agencies’ use of AI to protect rights and safety. Efforts will be made to help agencies acquire AI products and services more rapidly and efficiently, and an AI talent surge will be initiated to enhance government capacity in AI-related fields.

The executive order signifies a major step forward in the US towards harnessing the potential of AI while safeguarding individuals’ rights and security.

“As we advance this agenda at home, the Administration will work with allies and partners abroad on a strong international framework to govern the development and use of AI,” wrote the White House in a statement.

“The actions that President Biden directed today are vital steps forward in the US’ approach on safe, secure, and trustworthy AI. More action will be required, and the Administration will continue to work with Congress to pursue bipartisan legislation to help America lead the way in responsible innovation.”

The administration’s commitment to responsible innovation is paramount and sets the stage for continued collaboration with international partners to shape the future of AI globally.

(Photo by David Everett Strickler on Unsplash)

See also: UK paper highlights AI risks ahead of global Safety Summit

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 Cyber Security & Cloud Expo and Digital Transformation Week.

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

The post Biden issues executive order to ensure responsible AI development appeared first on AI News.

Their new research report, The Generative AI Tipping Point, sheds light on the challenges faced by organisations as generative AI technology becomes more prevalent in the workplace.

The report delves into how organisations are dealing with the use of generative AI tools, revealing a significant cognitive dissonance among IT and security leaders. Astonishingly, 73 percent of these leaders confessed that their employees frequently use generative AI tools or Large Language Models (LLM) at work. Despite this, a staggering majority admitted to being uncertain about how to effectively address the associated security risks.

When questioned about their concerns, IT and security leaders expressed more worry about the possibility of inaccurate or nonsensical responses (40%) than critical security issues such as exposure of customer and employee personal identifiable information (PII) (36%) or financial loss (25%).

Raja Mukerji, Co-Founder and Chief Scientist at ExtraHop, said: “By blending innovation with strong safeguards, generative AI will continue to be a force that will uplevel entire industries in the years to come.”

One of the startling revelations from the study was the ineffectiveness of generative AI bans. About 32 percent of respondents stated that their organisations had prohibited the use of these tools. However, only five percent reported that employees never used these tools—indicating that bans alone are not enough to curb their usage.

The study also highlighted a clear desire for guidance, particularly from government bodies. A significant 90 percent of respondents expressed the need for government involvement, with 60 percent advocating for mandatory regulations and 30 percent supporting government standards for businesses to adopt voluntarily.

Despite a sense of confidence in their current security infrastructure, the study revealed gaps in basic security practices.

While 82 percent felt confident in their security stack’s ability to protect against generative AI threats, less than half had invested in technology to monitor generative AI use. Alarmingly, only 46 percent had established policies governing acceptable use and merely 42 percent provided training to users on the safe use of these tools.

The findings come in the wake of the rapid adoption of technologies like ChatGPT, which have become an integral part of modern businesses. Business leaders are urged to understand their employees’ generative AI usage to identify potential security vulnerabilities.

You can find a full copy of the report here.

(Photo by Hennie Stander on Unsplash)

See also: BSI: Closing ‘AI confidence gap’ key to unlocking benefits

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 Digital Transformation Week.

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

The post Enterprises struggle to address generative AI’s security implications appeared first on AI News.

Raz shared insights from his extensive career, including his tenure as technical director for a web application firewall company. This role exposed him to the rise of the “Cyber Dragon” and Chinese cyberattacks, inspiring him to explore the offensive side of cybersecurity. During this time, he not only developed defence tools, but also created attack tools that would later be adopted by the Anonymous hacker collective.

“The perfect cyber weapon”

One of the most intriguing aspects of Raz’s presentation was his exploration of “the perfect cyber weapon.” He proposed that this weapon would need to operate in complete silence, without any command and control infrastructure, and would have to adapt and improvise in real-time. The ultimate objective would be to disrupt critical systems, potentially even at the nation-state level, while remaining undetected.

Raz’s vision for this weapon, though controversial, underscored the power of AI in the wrong hands. He highlighted the potential consequences of such technology falling into the hands of malicious actors and urged the audience to consider the implications seriously.

Real-world proof of concept

To illustrate the feasibility of his ideas, Raz shared the story of a consortium of banks in the Netherlands that embraced his concept. They embarked on a project to build a proof of concept for an AI-driven cyber agent capable of executing complex attacks. This agent demonstrated the potential power of AI in the world of cybercrime.

The demonstration served as a stark reminder that AI is no longer exclusive to nation-states. Common criminals, with access to AI-driven tools and tactics, can now carry out sophisticated cyberattacks with relative ease. This shift in the landscape presents a pressing challenge for organisations and governments worldwide.

The rise of AI-enhanced malicious activities

Raz further showcased how AI can be harnessed for malicious purposes. He discussed techniques such as phishing attacks and impersonation, where AI-powered agents can craft highly convincing messages and even deepfake voices to deceive individuals and organisations.

Additionally, he touched on the development of polymorphic malware—malware that continuously evolves to evade detection. This alarming capability means that cybercriminals can stay one step ahead of traditional cybersecurity measures.

Stark wake-up call

Raz’s presentation served as a stark wake-up call for the cybersecurity community. It highlighted the evolving threats posed by AI-driven cybercrime and emphasised the need for organisations to bolster their defences continually.

As AI continues to advance, both in terms of its capabilities and its accessibility, the line between nation-state and common criminal cyber activities becomes increasingly blurred.

In this new age of AI-driven cyber threats, organisations must remain vigilant, adopt advanced threat detection and prevention technologies, and prioritise cybersecurity education and training for their employees.

Raz’s insights underscored the urgency of this matter, reminding us that the only way to combat the evolving threat landscape is to evolve our defences in tandem. The future of cybersecurity demands nothing less than our utmost attention and innovation.

Want to learn more about cybersecurity and the cloud from industry leaders? Check out Cyber Security & Cloud Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with AI & Big Data Expo Europe.

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

The post Cyber Security & Cloud Expo: The alarming potential of AI-powered cybercrime appeared first on AI News.