As the conversation around generative AI vs responsible AI enters the public sphere, the two terms are often misunderstood as being at odds. We explain the difference between them and how generative AI can actually be used to make any AI more responsible.
In recent years, we’ve witnessed remarkable breakthroughs in the field of AI. These advances have led to the emergence of new words and concepts that are now becoming common language to the general public. The latest example is ChatGPT’s update to the language model GPT-4o, which you simply can’t avoid in online media.
Two terms that have become prominent during this development are responsible AI and generative AI. It’s crucial to recognize that actually, there is no generative AI vs responsible AI, as these terms are not antagonistic.
Generative AI describes a particular ability of some AI models and systems to produce fresh text, graphics, code, and other data outputs. Responsible AI, on the other hand, is an approach. It is a human-driven comprehensive strategy and set of guidelines for creating AI systems morally and reducing any hazards to people, companies, and society.
Despite being separate, these two ideas have a significant overlap. As generative AI tools become more integrated into our lives, they must be built in a responsible way that adheres to ethical and safe standards.
AI with good morals
The term responsible artificial intelligence refers to the process of creating and deploying AI systems that are both ethical and trustworthy. It is about ensuring that artificial intelligence follows notions such as:
- Fairness and non-discrimination
- Transparency and explainability
- Privacy and data protection
- Human oversight and control
- Robustness and safety
The goal of responsible artificial intelligence is to reduce a variety of potential hazards and ethical considerations people are raising as valid points. These can include bias, a lack of accountability, invasions of privacy, and negative social consequences.
Organizations that adopt responsible AI take a proactive approach to identifying and addressing any potential downsides their AI systems may demonstrate.
AI that generates new ideas
Generative artificial intelligence refers to AI models that can generate new creative materials, like text, images, audio, code, and other forms of information.
Rather than only analyzing or classifying the data that is already available, generative AI models create new outputs based on the training data that they have integrated. It is only logical that the rise of gen-AI tools has raised many questions about human creativity and whether it is at risk.
Some of the most popular examples include language models such as OpenAI’s GPT-3.5 and -4 or Anthropic’s Claude 3, which are capable of writing paragraphs of text; image generators like Stable Diffusion, which create one-of-a-kind images based on text descriptions; AI systems that generate code like GitHub Copilot; and the upcoming AI tools that actually create music, films, and other forms of media. It is even possible now to generate your own TV series, scripts, and virtual actors, which has been a contested issue in Hollywood over the recent years.
Generative AI vs responsible AI – the overlap
While responsible AI focuses on developing AI systems that are safe, ethical, transparent, and beneficial to society, and generative AI focuses on creating novel content like text, images, audio, etc., there is indeed a meaningful overlap between the two.
As generative AI systems become more advanced and widely used, they must be developed and deployed responsibly inside companies.
Responsible AI represents a counterbalance to the irresponsible use of generative AI, which could pose significant risks – it could perpetuate societal biases, be used to generate fake news and spread disinformation at scale, or enable highly realistic “deepfake” content, for example.
As generative AI grows more powerful, the potential for misuse and harm increases, and ethical considerations must be a key focus.
How to use generative AI to make any AI responsible
Training generative models on the internet data can pose a number of societal dangers. To ensure that generative AI is dependable, valuable, and safe, we must develop it with responsible AI principles at its core.
This means carefully curating training data, incorporating human oversight, maintaining transparency, and aligning the AI’s goals and model outputs with human values and ethical considerations. It’s about empowering humans to build, deploy, and monitor the necessary oversight in the generative AI-responsible AI dance, as much as it is about leveraging the technology for driving speed, efficiency, and ideation.
However, generative AI is not just a technology that needs to be made responsible – it can also be a powerful tool for making other AI systems more responsible.
The same techniques used to generate realistic text, images, and other media can be applied to create clear explanations of how AI systems work, detect and mitigate biased data and decisions, and even generate synthetic training data to protect individual privacy.
By combining generative AI with the ethical principles of responsible AI, we have the opportunity to create artificial intelligence that is not only incredibly capable but also safe, ethical, and trustworthy.
As we continue to push the boundaries of what AI can do, it is essential that we prioritize responsibility and safety at every step. Only by developing generative AI responsibly can we unlock its full potential to benefit society while mitigating its potential risks. The intersection of generative AI and responsible AI is not just important – it is essential for building an AI-powered future that we can all depend on.
Generative AI vs responsible AI – why not both?
As we’re witnessing the rapid development of artificial intelligence, it will be more important than ever to examine the relationship between generative AI vs responsible AI. Generative AI models hold a lot of potential, including the ability to accelerate scientific discovery while also empowering human creativity and expression. Nonetheless, in order to realize this promise in a safe and ethical manner, we must adopt responsible AI values such as responsibility, transparency, and human control.
Rather than competing, ethical behaviors and generative skills should complement one another as essential components of trustworthy artificial intelligence. After that, we will be able to fully grasp AI’s potential to have a positive impact on our society.
