Ethics in the Age of AI

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We know that AI increases productivity, but at what cost? 

 

With Nvidia's market cap soaring into the trillions and Apple partnering up with OpenAI to embed ChatGPT into their latest iPhones, it’s safe to say AI is taking over the world.

But amidst this technological gold rush, I can’t help but notice that the ethics of developing these models often get shoved onto the back burner.

Take Amazon, for example:

They had a hiring tool powered by an AI model designed to select the best candidates. 
Sounds highly productive, right? Well, it favored male applicants due to the skewed dataset it was trained on.

Sure, these models can learn and improve over time with reinforcement, but here’s my question: 
how long will that take?

The output of these models are only as good as their inputs. 

I’m no AI expert, but I am a pretty sharp observer and I believe that big tech companies need to strike a balance between raking in the profits and ensuring fairness.

Especially now, when these models are making life-altering decisions based on vast datasets that no human could ever hope to sift through.

With that said, let’s dive into the dimensions of AI ethics and some trade-offs of each: 

Privacy

This includes transparent data collection practices, user consent, and mechanisms for individuals to access and modify their data.

Trade-off:  Stricter privacy controls might limit the effectiveness of AI models in some applications.


Fairness

Ensuring AI models are unbiased and do not discriminate against any group of people. 

Trade-off: Achieving perfect fairness can be computationally expensive and time-consuming. 


Inclusion

Designing AI systems that consider the needs of diverse populations and avoid perpetuating social inequalities.

Trade-off: Finding diverse datasets for training can be challenging.


Accountability

Holding developers of AI systems responsible for their impact and potential harms. 


Trade-off: Ensuring accountability can be complex when multiple parties are involved in developing and deploying an AI system.


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