“Who created Artificial Intelligence (AI)?
It is we, Humans.
If we are responsible for creating AI.
Then, why can’t we create a responsible AI?”
Why do we have so much concern regarding the responsibility of AI towards society and humanity? We do have because of its complexity of operation and impact. The impacts can be positive or negative, however humans should know what they are using for and the possible outcomes? If there is something good for humanity, it should be openly discussed and easy for all to understand.
We have been dependent on machines in recent decades due to its efficiency and intelligence level and its impact on our lives. We all have seen a drastic positive change in our lives after using AI in some ways. It is because of high internet speed, adoption of mobiles and data usage. It has increased our productivity levels everywhere. AI has impacted our lives and we have become more dependent on it.
At this juncture, don’t you think
If AI goes irresponsible, what will happen to our lives?
Will you be able to operate the way you are doing now?
Will you be able to trust on AI and its positive impact?
Why does it matter so much?
There are certain industries like finance and HR where you need to be in compliant with legal, business and technology requirements across the world. AI is no different. When we talk specifically about HR, we have so many activities that we look at e.g. employee safety, employee policies, their health, recruitment standards, pay scale, salary raise and their data privacy. AI is being used in HR these days and we must maintain the ethics across roles, responsibilities, and departments. This is a hard-core business need now. These are the below mentioned rules that we should be caring for:
The models should be designed and aligned with the purpose of the business. We need to ensure that the algorithm should not have any unintended bias within and should have a human element with it. It should be like Human-in-the-loop system.
We should be sustainably practice building software and apply models on a diverse data set. We should be able to reuse the data efficiently and should have less model maintenance. Click here to read more about our sustainable approach.
The data must be in a secure server with a proper control mechanism and infrastructure. Also, we need to ensure that the data is well-managed and timely audited.