AI outputs are simply reflections of human-biased inputs.
gettyAs I’ve mentioned, one of the biggest problems emerging from the AI revolution has been the thorny question of AI bias. We’ve already seen AI models used for predictive policing accused of perpetuating systemic racism, and similar concerns have plagued AI tools used for recruitment and in many other areas.
Now, GenAI tools like ChatGPT are making a bad situation worse, creating text and images that are riddled with implicit racial and gender biases.
These are serious problems, and they’re ones that all leaders will have to contend with in the coming weeks and months.
As we do so, though, it’s important to remember that when it comes to algorithmic biases, the real fault lies not in our algorithms but in ourselves. AI tools don’t create bias — they reveal them by replicating the reality of the societies and organizations that they serve.
Time to Look Inward
This means, first and foremost, that the rapid spread of AI requires us to reconsider our data sources. If we aren’t getting the right results, are we drawing in the wrong inputs? Unless we’re cautious about handling things, bad-quality data will almost always lead to bad-quality outcomes.
This is something we should try to think about, not just in terms of our AI tools but also in terms of ourselves as individuals. When I face a tough problem, I ask myself: could I find a better solution if I cast a broader net and sought new insights and possibilities?
Very often, deliberately reaching out to new sources of knowledge or seeking new perspectives helps me unlock smarter and more effective solutions to problems that had previously felt insurmountable.
Surface Your Biases
Seeking out fresh inputs is only one piece of the puzzle, though. We also need to surface, acknowledge, and challenge the biases we all carry with us.
Biases aren’t always a bad thing, of course. If I were to insult you every time we met, you might develop a bias against spending time with me — as well as you should! Biases of this kind can often protect us or serve as a mental shortcut to help us make faster and smarter decisions as we deal with the complex world.
But biases can also lead us astray unless we’re actively working to elevate our knowledge mindfulness and diversify our inputs to make judgments and decisions.
Leverage Your Knowledge Mindfulness
Just like AI tools, humans can develop unwanted biases unless they actively work to enrich their connections with themselves and the world around them and to seek out diverse perspectives from people of different genders, backgrounds, skill sets, ages, and more.
The good news is that, unlike AI algorithms, humans are active agents capable of reflecting course-correcting and improving. To solve for bias—both in our algorithms and in ourselves—we must keep actively working to improve and expand the totality of the available knowledge.
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{Categories} *ALL*,_Category: Implications{/Categories}
{URL}https://www.forbes.com/sites/forbesbooksauthors/2023/11/27/to-beat-algorithmic-bias-start-by-looking-inward/{/URL}
{Author}Laila Marouf, Forbes Books Author{/Author}
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