In day to day life, AI has become an important part of lives. As humans, we have some responsibilities to fulfill. It is the same for AI where AI follows some guidelines, principles and policies which are responsible for the organization so it can reflect its values and mission.
We humans may forget our responsibilities but AI doesn’t. It is much more accountable than humans to make sure that it is more responsible than humans. We create principles and policies that are accurate and friendly towards humans.
What is responsible AI?
Let us see what is responsible AI. Responsible AI is like teaching a robot good manners.
It means making sure that when we build and use AI, it is fair to everyone and does not cause harm. Imagine if a robot could learn from peoples action like a kid learning from grownups. Responsible AI teaches robots to be accountable, fair and respectful, just like we teach kids to be polite.
Its about making sure AI does not discriminate, respects privacy and follows rules like not sharing secrets. Just like we want our kids to grow up to be a good and responsible citizen, we want AI to be a good and responsible digital citizen too.
Importance of responsible AI
Responsible AI has many important aspects.
Some of them will help responsible AI build trust with customers and stockholders. It also improves operational and communication efficiency and can help drive revenue. Responsible AI can reduce issues such as AI being biased or unsafe and ensures that it is designed, deployed and used ethically and legally.
It also ensures consumers privacy, discrimination and harm prevention. The main goal of responsible AI is to employ AI in a safe, trustworthy and ethical fashion way.
Principles of responsible AI
Let see few common principles of responsible AI that every organization follows such as fairness, reliability and safety privacy and security accountability and transparency.
Fairness AI system should treat all people fairly. They shouldn’t be biased by giving different answers for different organizations and should be accurate with the information they provide. If the AI is not fair, it will have trust issues with the consumers reliability and safety.
AI system should perform reliably, consistently and safely under normal circumstances and in unexpected conditions. To make AI reliable and safe, it is important to think about how we could go wrong, how the AI might react, how people can fix it quickly and always prioritize keeping humans safe. Privacy and security AI systems should be secure, respect privacy and resist attack.
Just like we have rules about how we can use someone’s personal stuff, AI system have rules about how they can use people’s personal information. These rules are there to ensure that your information stays safe and isn’t misused. Accountability Accountability in responsible AI ensures that there is a clear line of responsibility for the deployment, development and outcome of AI system.
The more advanced and independent AI system becomes, the more accountable the organization behind them is to ensuring that they are used ethically and responsibly, especially when people safety is at stake. Transparency AI system should be understandable. Achieving transparency ensures that AI processes and decisions are transparent, so it is clear how and why a decision was made.
Implementation and working of responsible AI
There are few steps to implement responsible AI.
- Step 1: defining goals we should make sure what tasks the AI should perform according to the organization and make sure that it meets their expectations and help them achieve their goals.
- Step 2: collecting data. This step collects the requirement and information for the AI and feeds it with the data.
- Step 3: selection of tools. Different tools are used so that the AI can enhance its capability, enabling it to perform specific tasks more effectively, accurately and efficiently.
- Step 4: algorithm creation or model selection creating models for responsible AI means designing and selecting system that are fair, ethical and do not cause harm.
- Step 5: training the algorithm or model. In this step, we teach the system to make fair and ethical decisions without causing harm.
- Step 6: evaluation of AI system it checks to ensure that the system makes fair and ethical decisions.
- Step 7: deployment of AI solution this step ensures that the AI system operates fairly and ethically in real world situation.
Working of responsible AI
Responsible AI works by different principles and rules, being fair, transparent, safe, ethical while respecting people’s privacy. Different companies set some standards that they followed to make AI more responsible.
The AI learns from the pattern and features of data so that it can be more responsible and not biased when giving information.
Difference between responsible AI and unethical AI
Let see what is the difference between responsible AI and unethical AI. Responsible AI it aims to create AI for safe, ethical and transparent interaction with users, whereas ethical AI aims to create AI that makes morally sound decisions and treats all users fairly.
Responsible AI can be applied to various sectors, from healthcare to finance, whereas ethical AI has values such as fairness, accountability and transparency. Responsible AI strives for a balanced experience that is both ethical and efficient, whereas ethical AI prioritizes a fair and unbiased experience, potentially at the expense of speed. Responsible AI involves a multidisciplinary approach, including legal experts for governments. It is same for ethical AI, where it also requires a multidisciplinary team that focuses more on ethics and moral awareness.
Example of few companies embracing responsible AI
Let see some of the examples where a responsible AI are used. Microsoft and IBM have each developed their own set of rules and guidelines to make sure that the AI technologies they use and create a responsible and fair Microsoft.
It has its AI committee and Office of Responsible AI, which sets companies wide rules for responsible AI. They provide guidelines for how humans and AI should interact, how AI should be designed inclusively, and how to ensure fairness in AI system. They also have templates for things like data sheets and guidelines for AI security.
So let see how the IBM has used a responsible AI IBM has its own ethical board focused on AI, their work on trust, transparency and ethical use of AI. They also provide resources for everyday ethics in AI, supports open source AI project, and do research to make AI more trustworthy. Now, to conclude this video, I would like to say responsible AI makes sure that AI systems are fair, safe and transparent.
Many companies have created rules and guidelines to ensure that AI is used ethically and does not discriminate. They do this by setting standards for AI. To know more about this video, visit our course, the link to which is given in the description box below.
If you enjoyed this blog post, you can share it with your network. It will only take a few seconds, but it will mean the absolute world to me.
Let’s keep in touch.
