The hidden prejudice of AI: why algorithms can be more biased than humans

The hidden prejudice of AI: why algorithms can be more biased than humans

The algorithmic bias bomb | AI this week in the news; use cases; tools for the techies


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Fast access to our weekly posts (tap the links for fast access):

??? Who controls the future? The AI power grab and its societal impact

?? Human-AI collaboration and governance (online course)

?? Maildrop 29.10.24: The future of LLM-powered keyloggers (slides inside)

?? How to build with AI agents | The tech stack of virtual agents

?? Enterprise AI and trust: building confidence through safety and transparency

?? Case study: AI just helped someone sue their landlord without a lawyer


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The prejudices of our past taint the very algorithms we are building to reshape our world.

LLMs trained on massive datasets reflecting existing societal biases can inadvertently perpetuate and even amplify discrimination, particularly against marginalized groups.

This is not a mere technical glitch but a reflection of our deeply ingrained societal prejudices seeping into the very core of our technological creations. ?

Imagine an AI-powered hiring system that favors specific demographics over others, perpetuating existing inequalities in the workplace.

Or a loan application algorithm that systematically denies credit to individuals from specific communities, reinforcing historical patterns of economic disadvantage.

These are not hypothetical scenarios but the potential consequences of deploying biased AI systems in critical decision-making processes.

We must grapple with the question: Can we truly create a just and equitable society if the tools we use to shape it are inherently biased?

[Continue reading on Wild Intelligence]


The essence of this weekly publication is inherently embedded in this mindset: to bridge the gap between traditional mechanisms and increasingly sophisticated actions.

Each post is specially conceived to help business leaders frame the context of Decision Intelligence?in the AI era. As I deepen my work, I bring new things I am excited to share.

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Fast access to our weekly posts (tap the links for fast access):

??? Who controls the future? The AI power grab and its societal impact

?? Human-AI collaboration and governance (online course)

?? Maildrop 29.10.24: The future of LLM-powered keyloggers (slides inside)

?? How to build with AI agents | The tech stack of virtual agents

?? Enterprise AI and trust: building confidence through safety and transparency

?? Case study: AI just helped someone sue their landlord without a lawyer


(New weekly) Explore more on Wild Intelligence [Extended]

AI-driven threat intelligence: enhancing detection and response


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More from the Wild Intelligence week


???Poll, vote now: Will AI make human creatives obsolete?

While AI undoubtedly challenges human creatives, it also presents opportunities for collaboration and innovation.

The key lies in recognizing the unique strengths of both human and artificial intelligence and finding ways to leverage their respective capabilities to push the boundaries of artistic expression.

Ultimately, human creativity may be valued for its ability to connect with and inspire us on a deeply human level, something that AI may never fully replicate:

A) Yes, AI will eventually replace human artists entirely.

B) No, AI will serve as a tool to enhance human creativity.

C) AI will lead to new forms of art and collaboration, but human creativity will diminish.

D) AI and human artists will coexist, but the art world will change fundamentally.


?? Human-AI collaboration and governance (online course)


The "Building safe intelligence systems" delves into the critical aspects of AI safety and security, providing you with the knowledge and tools to navigate this rapidly evolving landscape.

The "Building safe intelligence systems" delves into the critical aspects of AI safety and security, providing you with the knowledge and tools to navigate this rapidly evolving landscape. We explore:

  • The ethical foundations of AI: Understanding the values and principles that should guide AI development and deployment.
  • Mitigating AI threats: Identifying and addressing potential biases, vulnerabilities, and unintended consequences.
  • Building robust and resilient AI systems: Developing secure AI architectures and implementing safeguards against adversarial attacks.
  • Fostering collaboration and transparency: Creating open and inclusive AI governance and knowledge sharing processes.

[Continue reading on Wild Intelligence]


?? Maildrop 29.10.24: The future of LLM-powered keyloggers (slides inside)

LLMs have the potential to revolutionize various fields, including cybersecurity. While LLMs can be used to enhance security measures, they can also be exploited by malicious actors to create more sophisticated and evasive attacks.

One such threat is the integration of LLMs with keyloggers.

LLMs have the potential to revolutionize various fields, including cybersecurity. While LLMs can be used to enhance security measures, they can also be exploited by malicious actors to create more sophisticated and evasive attacks.

One such threat is the integration of LLMs with keyloggers.

[Continue reading on Wild Intelligence]


?? How to build with AI agents | The tech stack of virtual agents


Under the hood of every engaging virtual agent lies a complex network of interconnected technologies.

? With the rapid advancement of AI, will building virtual agents eventually become as simple as assembling Lego blocks, democratizing access to this powerful technology?

Under the hood of every engaging virtual agent lies a complex network of interconnected technologies.

? With the rapid advancement of AI, will building virtual agents eventually become as simple as assembling Lego blocks, democratizing access to this powerful technology?

[Continue reading on Wild Intelligence]


?? Enterprise AI and trust: building confidence through safety and transparency


In an era of increasing AI adoption, trust is paramount.

Customers, employees, and the public at large need assurance that AI systems are safe, reliable, and used ethically.

Transparency and explainability are technical challenges and essential ingredients for building and maintaining trust in AI.

In an era of increasing AI adoption, trust is paramount.

Customers, employees, and the public at large need assurance that AI systems are safe, reliable, and used ethically.

Transparency and explainability are technical challenges and essential ingredients for building and maintaining trust in AI.

"The best way to predict the future is to invent it." - Alan Kay (Computer Scientist)

[Continue reading on Wild Intelligence]


?? Case study: AI just helped someone sue their landlord without a lawyer


The legal landscape is undergoing a seismic shift, driven by the transformative power of artificial intelligence. No longer confined to the dusty tomes of law libraries and the exorbitant fees of seasoned attorneys, legal knowledge is becoming democratized, accessible to anyone with an internet connection.

The legal landscape is undergoing a seismic shift, driven by the transformative power of artificial intelligence.

No longer confined to the dusty tomes of law libraries and the exorbitant fees of seasoned attorneys, legal knowledge is becoming democratized, accessible to anyone with an internet connection.

[Continue reading on Wild Intelligence]


?? AI news and resources: the things to read, ideas, and everything else

  • #Anthropic has released a beta version of its AI model that can control your screen and perform tasks within apps. This agent-based approach puts the user in charge of defining tasks and checking accuracy. A key question raised is whether LLMs should be the primary interface or act as supporting API calls within a larger system. [LINK]
  • #Microsoft has added a layer of ‘autonomous agents’ to some of its enterprise tools, and Salesforce is promoting the same. New autonomous agents scale your team like never before. [LINK]
  • #Perplexity aims to replace traditional search engines by directly answering user queries and using LLMs to summarize relevant web pages. While it boasts over 100 million weekly queries, this translates to roughly 1.5 million daily users, suggesting a niche but growing user base. [LINK]


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LinkedIn posts

Some of the things I share:

  • VC investment in startups is rebounding in 2024 after a slow 2023. Hardware, SaaS, and Adtech are leading the way with significant funding increases. [LINK]
  • A few thoughts on Microsoft CEO Satya Nadella's advocating for re-evaluating copyright laws to facilitate AI development, citing Japan's flexible approach as a model. [LINK]


Last week's news:

The robots are coming: is AI the ultimate disruptor of society?


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Dawn-joy Leong

PhD Autism, Neurodiversity and Multi-Art Praxis. Keynote Speaker; Author; Installation Artist; MusicComposer; Consultant. Salzburg Global Fellow. Co-founder & Director, K9 Assistance Singapore.

3 周

Insightful. AI needs to be trained on more diverse data for encompassing, comprehensive critical perspectives. The danger is bias amplification. Thanks for this, Tony!

Gillian Marcelle, PhD

CEO and Founder, Resilience Capital Ventures LLC

3 周

Your clear explanations are useful. “This is not a mere technical glitch but a reflection of our deeply ingrained societal prejudices seeping into the very core of our technological creations.” Thanks for your leadership Yael Rozencwajg

Yael Rozencwajg

Founder and CEO @ Wild Intelligence | AI safety, cybersecurity, enterprise AI mission

3 周

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