A Dive into the Heart of AI Ethics: Balancing Innovation and Responsibility

2-3 min read • 


Since the beginning of 2023, AI has been taking the world by storm, from running models such as ChatGPT—the main attraction of Artificial Intelligence's power—to even pioneering autonomous vehicles. 

However, as awe-inspiring as these advancements in our technology may seem,  it is important to note the ethical considerations that come with it. 


The Main Concern 

One of the most concerning faucets of Artificial Intelligence ethics is the bias within these AI models. AI systems are trained on sets of data, and these systems go through this data and make connections as to what is "right" and what is "wrong." 

Think about it—if a developing baby was taught that a certain minority is "bad" and "ugly," then the child will live their whole life having a stereotype against that minority. 

The same principle applies to AI models as well, especially given that they are built to mimic how us humans learn and develop connections. If an AI language model is trained with linguistic data favoring one race over another, then the AI will inadvertently discriminate against the latter, leading to a biased AI model.

The main problem stems from the data that AI models are trained on. However, almost every person on Earth has bias to some degree based on their upbringing, as much as they might deny it. As such, when AI models are trained on these human-made works, they are bound to pick up on the bits of bias within them, taking it as important material to base its knowledge base on.

If this problem is not taken care of, it can lead to many problems down the line— not just with the AI industry, but on a much larger scale as AI is integrated into our daily lives. For example, AI can be used in the criminal justice system, it can be used as a tool for medical experts to use to discover massive breakthroughs in medicine, it can be used as a teaching resource in schools, and it has so many more uses. If biases find their way into these areas, then the result would be, to put it mildly, devastating.


Potential Solutions

The responsible development of Artificial Intelligence is built upon a set of guidelines and practices that prevent a developing AI model from displaying signs of bias in their outputs and helping mitigate any bias that may previously exist. 

One way to responsibly build AI models is by assembling diverse development teams of different backgrounds and cultures. These teams will work together to instill values from various backgrounds so that the AI will learn to show respect to all races and learn the importance of all backgrounds.

Another way to help facilitate the development of responsible AI systems is to clearly define ethical guidelines in the AI's base code to encourage a healthier development. This ethical framework will serve to let the AI itself know what is right and wrong in terms of bias.

The public can also take part in this process— by being transparent with the general population on how an AI is trained and structured, developers can help the users make better judgements on the outputs of the model and possibly suggest areas of improvement with the public's collective diversity.

That being said, published AI models should be continuously monitored to ensure the viability of the outputs and to detect any post-production bias and / or ethical concerns. Finding and correcting these concerns before an AI can extrapolate on these problems and integrate it into its self learning can help the AI quickly learn from its mistakes and learn not to make the same mistake again, one of the kinks of an AI. 


Conclusion:

As AI develops in our society, we must be fully cognizant about how it develops to prevent any long-term issues down the line. Artificial intelligence has many uses in our society, and we must first learn to make AI fully incorrigible before we should advance it further. The development of AI in our world is inevitable, and with its exponential and potentially limitless growth, only a short span of time remains between the time you finish reading this, and the next AI breakthrough.


Sources:

https://hackernoon.com/the-ethics-of-ai-addressing-bias-and-responsible-ai-development

https://hammadabbasi.com/blogs/a-deep-dive-into-ai-safety-and-ethics-utilizing-openais-moderation-apis.html

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