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🚧 Navigating Biased Data in the Age of AI
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🚧 Navigating the Hazards of Biased Data in the Age of AI.
🔑 AI in your daily life? Consider these key points.
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🧰 AI Tools of the Day
💀🎨 "Is this Photoshop's slow death?
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💪🏽 Miscellaneous and AI updates
Act as if - A collection of 100+ prompts you can try today.
🚧 Navigating the Hazards of Biased Data in the Age of AI
The rapid rise of AI has brought unprecedented technological advances, catching us off guard with its speed and impact. As AI applications become ingrained in our lives, it's essential to comprehend their uses, risks, and implications.
Artificially intelligent machines are not exactly programmed.
As Mo Gawdat, Former Chief Business Officer of Google [X], shares on his book “Scary Smart” these machines comb through vast quantities of data, seeking patterns that will foster the growth and evolution of their intelligence.
“Eventually, they become original, independent thinkers, less influenced by the input of their original creators and more influenced by the data we feed them.”
A key lesson from Scary Smart is: “The code we now write no longer dictates the choices and decisions our machines make; the data we feed them does.”
Entrepreneurs and corporations rush to unveil AI models, often overlooking data vetting and examination. This raises concerns about biased and manipulated decision-making, skewed information consumption, and potential harm to our well-being.
In "Weapons of Math Destruction," Cathy O'Neil explores algorithms' impact, labeling some as "Weapons of Math Destruction" (WMDs). These algorithms perpetuate inequality, unfairness, and discrimination, affecting sectors like education, employment, finance, and criminal justice.
WMDs reinforce biases, disproportionately harm marginalized groups, and limit opportunities for individuals. O'Neil calls for greater awareness, regulation, and responsible algorithmic decision-making.
In healthcare, the World Health Organization (WHO) warns about using AI-generated language models (LLMs) without caution. Risks include biased data, inaccuracies, health equity concerns, and the spread of disinformation.
WHO urges evidence gathering, ethical principles, and governance in LLM use, emphasizing patient safety alongside technology firms' commercialization efforts.
As we navigate the age of AI, balancing its potential with challenges is vital. Ethical practices must guide AI's development, ensuring its positive impact while mitigating risks and safeguarding fundamental values.
🔑 We are all using AI in our daily life, consider these key points:
1. Educate yourself: Understand AI's capabilities, limitations, and risks to make informed decisions.
2. Question data: Be skeptical of the quality and biases in AI's training data.
3. Promote diversity: Advocate for inclusive datasets to reduce bias and ensure fairness.
4. Demand accountability: Hold developers and companies responsible for their AI systems and demand transparency.
5. Stay informed: Keep up with AI developments, risks, and ethical considerations.
6. Protect your data: Be mindful of privacy and security when using AI applications.
7. Report concerns: Raise awareness of bias or unethical practices in AI systems.
By being educated, doing your own research and being engaged, we can shape responsible AI use in our lives.
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💀🎨 "Is this Photoshop's slow death?
Meet DragGAN: AI's Groundbreaking Image Manipulation Tool" (link)
New AI research has introduced a powerful image manipulation tool that allows users to click and drag elements within an image to change their appearance. Unlike traditional methods like Photoshop's Warp tool, this new system utilizes AI to regenerate the underlying objects, enabling users to alter dimensions, rotate subjects as if they were 3D models, and even adjust reflections and heights within landscapes with just a few clicks.
The research team behind this model, called DragGAN, emphasizes the significance of its user interface, offering flexibility and precision in image manipulation that previous AI methods lacked. While this is currently a demo and the full extent of its capabilities is yet to be evaluated, it showcases advancements in accessible image manipulation.
💪🏽 Miscellaneous and AI updates
Bill Gates says A.I. could kill Google Search and Amazon as we know them
Forrester predicts 2023’s top cybersecurity threats: From generative AI to geopolitical tensions
A.I. has spawned a ‘Game of Thrones’–style battle for what is a $800 billion opportunity over the next decade
Adarga, a London-based startup offering AI software for security risk intelligence, has raised $20 million
Parker89 has led a £7.5 million Series A for Orbital Witness. The startup uses generative AI to improve the due diligence process for buying properties.
Act as if - A collection of 100+ prompts you can try today.
My Favorite (just copy, tweak and paste.) (link)
Generate digital startup ideas based on the wish of the people. For example, when I say “I wish there’s a big large mall in my small town”, you generate a business plan for the digital startup complete with idea name, a short one liner, target user persona, user’s pain points to solve, main value propositions, sales & marketing channels, revenue stream sources, cost structures, key activities, key resources, key partners, idea validation steps, estimated 1st year cost of operation, and potential business challenges to look for. Write the result in a markdown table.
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Great post. I really the 7 Key Points. I feel like I may (may!) be doing a decent job on 1,2, and 5 - but need to step up my game all round and especially on the remaining four.