The rapid rise of #AI is creating a new digital divide, threatening to amplify historical biases in high-stakes decisions. AFCEA corporate member Fearless explores how embracing diversity in AI development can transform this challenge into an opportunity. By prioritizing diverse teams and critically examining training data, we can harness AI's potential to narrow disparities instead of widening them. Discover how fostering inclusion in AI can create a more equitable digital future for all in this insightful article. https://lnkd.in/g9u_vKee#artificialintelligence
To close the digital divide, diversity and inclusion must become a strategic imperative. Not only within government agencies, but also the contracting community that serves them and the technology sector as a whole.
Only by building teams as diverse as the public we serve can we design AI and digital services that work for all.
The potential of AI to either amplify biases or empower all is a critical issue that deserves our full attention. Your call to action for building diverse teams and conducting regular audits of AI models is a vital step towards ensuring fairness and equity.
The rapid rise of #AI is creating a new digital divide, threatening to amplify historical biases in high-stakes decisions. AFCEA corporate member Fearless explores how embracing diversity in AI development can transform this challenge into an opportunity. By prioritizing diverse teams and critically examining training data, we can harness AI's potential to narrow disparities instead of widening them. Discover how fostering inclusion in AI can create a more equitable digital future for all in this insightful article. https://lnkd.in/g9u_vKee#artificialintelligence
Building a more equitable future with AI is possible, but it requires intentional action.
In his new article, Fearless COO Joe Paiva explores how AI can be both a catalyst for equity and a perpetuator of historical biases. He challenges us to think critically about how we design and deploy AI to ensure it serves all communities.
Interested in building a more equitable future with AI? Read Joe's full article here:
https://hubs.la/Q02F_FPr0#AI#DigitalDivide#EquityInTech
It's no secret that the data fed into AI algorithms often reflects the biases and inequalities present in society. From hiring practices to healthcare decisions, these biases can have far-reaching consequences, perpetuating inequality and hindering progress. Let's talk about it.
#AI#GenderInclusion#Technology
Health Equity and Generative AI by Dr. Ivor Horn
In the latest article from Google Health, Dr. Ivor Horn explores how generative AI can advance health equity. Here are the key highlights:
Foundational Approaches to Equity Research: Google integrates Community-based Participatory Research (CBPR) to reflect the experiences of historically marginalized communities. This ensures that AI solutions are designed with a deep understanding of users’ social contexts. 🌍
Prioritizing Diverse Representation in Data: Google strives for inclusivity in data collection and model development. By partnering with the broader AI research community, they aim to set standards for diverse representation in data. 🤝
AI and Industry Partnerships: Collaborations with organizations like the National Institutes of Health (NIH) help Google expand their understanding of human diversity through projects like the Pangenome project. 🧬
Responsible AI Development: Google emphasizes the importance of responsible AI development to avoid exacerbating existing health inequities. They have developed frameworks to assess and mitigate biases in AI models. ⚖️
Why This Matters
AI Proficiency: The article showcases Google’s advanced use of AI to address complex health equity issues, demonstrating their proficiency in leveraging technology for social good. 💡
5.0 Leadership: Google’s approach exemplifies 5.0 leadership by integrating empathy, inclusivity, and ethical considerations into their AI strategies. 🌟
Detailed Strategies: The detailed strategies outlined, such as CBPR and diverse data representation, highlight Google’s commitment to thorough and thoughtful AI development. 📊
Empathy: At the core of these initiatives is a deep empathy for historically marginalized communities, ensuring that AI advancements benefit everyone. ❤️
As someone passionate about leveraging technology for social good, I’m excited to see how AI can further advance health equity.
Your Turn!
How do you think AI can make a difference in this field?
Share your thoughts in the comments!
#UKAIWWL#HealthEquity#GenerativeAI#AILeadership#EmpathyInTech#NLP#AIForGood 🚀💡
Link Here: https://lnkd.in/g3VMSd5i
Is AI Shaping the Future or Stuck in a Loop? I’ve collected employee Linkedin data on OpenAI, Anthropic, and DeepMind. With thousands of employees, these companies are at the helm, influencing not just industries but the entire world.
But here's the thing - there's a built-in bias.
We have too few people asking the crucial questions: Where can we go? Where do we want to go as a community? Where is the real transparency?
# Where They Studied: The AI workforce is sourced from elite universities. While this brings excellence, it also risks perpetuating a narrow perspective. Diversity in education can foster innovation in unforeseen ways.
# What They Are Skilled At: These professionals excel in machine learning, programming, data analysis, and AI research. Their technical prowess is unparalleled, but we must ensure that a diverse set of skills and perspectives are included to drive holistic innovation.
# What They Studied: Their academic backgrounds span computer science, engineering, mathematics, and related fields. While these disciplines are crucial, we also need insights from the humanities, social sciences, and other areas to address the broader implications of AI.
# Where They Live: Concentrated in major tech hubs, these experts drive AI development. But are we missing out on insights from different geographies and cultures? Broader representation could unlock new potentials.
# What They Do: From engineers to researchers, their roles shape the AI narrative. Yet, we need a holistic approach, integrating diverse voices and disciplines to ask - and answer - the bigger questions.
AI has the power to transform billions of lives. But to truly harness this potential, we need to break free from our echo chambers and build a more inclusive, visionary community.
Let’s challenge the status quo.
In what ways can we expand AI talent beyond traditional tech hubs?
It's no doubt that the rise of artificial intelligence (AI) is revolutionizing entire industries and when optimized to its full potential can have the ability to positively impact our everyday lives. Check out how AI can become a critical accelerator for inclusion and equality of opportunities across diverse communities.
#artificialintelligence#diversityandinclusion
See below for Dr. Wurth’s ideas for proactively reducing bias in AI. Because AI is everywhere, addressing bias in AI is going to be an emerging issue, especially within DEI work.
Research Leader | Advisor | Board member | Embedding data with empathy
AI is EVERYWHERE, being built faster than we can catch the harmful biases it creates. So how do we *proactively* reduce the bias in AI?
I am teaching a course on responsible AI and was delighted that nearly every group project mentioned that the AI tool they evaluated was built upon biased datasets. The data was often not even representative of the population it was intended to be used for. That’s a BIG problem.
So what can be done?
Most data that feds AI algorithms is what we call secondary data — scrapped or pulled from public sources, but not intentionally sampled for that AI use case. The unsexy work of fixing this is to be intentional about collecting primary data on populations who are often not captured. I’ve had the opportunity to work with the non profit Buddy System MIA and it surprised me how they have never been valued for their amazing data collection work among the most vulnerable and often omitted communities.
One way to reduce the bias in AI is elevating groups that are already collecting high quality data as a means to serve and support these underrepresented communities. Lets be more proactive in combatting bias.
If you’re working in AI and looking to reduce bias or are a non profit wishing to understand how to showcase or improve the value of your data, definitely reach out (here or or @ https://lnkd.in/dd5qkEJ6) as I’d love to collaborate.
Women contribute to AI research and innovations often to less fanfare than their male counterparts.
That’s why we’re shining a spotlight on 5 inspiring #WomenInTech that you should know about. https://bit.ly/3VZwrSm#ArtificialIntelligence#AI
Read the latest op-ed from Amanda Cage and Joseph Fuller in The Hill "In the Age of AI, We Need a System of Career Navigation for All". Let's seize the transformative power of #GenerativeAI for an equitable future! #CareerNavigationhttps://lnkd.in/grrp4kSC
Do you know what will futureproof you and your career?
Arguably there are some skills that women are typically more adept at than men irrespective of role - like empathy, alertness to bias, and other human-centric skills that will make them more employable in the future.
This article offers an interesting perspective but with the rate of change in AI, the research is somewhat out of date from 2021.
What do you think ?
#humaninteraction & #networking!
#futureofwork#AI#networking#PWN#Womensnetworks
To close the digital divide, diversity and inclusion must become a strategic imperative. Not only within government agencies, but also the contracting community that serves them and the technology sector as a whole. Only by building teams as diverse as the public we serve can we design AI and digital services that work for all.