As the demand for Artificial Intelligence(AI) based technology explodes, the demand for systems that can interact with people has also increased. However, creating such a system is not an easy task.
There are essentially four main challenges to be faced in the development of AI-powered tools.
Bridging the accuracy gap.
One of the most difficult tasks of creating AI systems is to ensure that it is aligned with user expectations as far as functionality is concerned. It is also necessary to ensure that the AI system’s results meet the intentions of the user. AI developers, on the other hand, are focused on expanding the data sets and data models and this can result in the results being not in line with the user expectations. One way to overcome this is to include human testers and by analysing their feedback AI developers can fine-tune their programs, and reduce the errors and unintended bias.
Incentivise those who work with AI.
One of the common problems faced is that people who use the AI system in their initial stages quickly abandon it when they find that the results are not of much value to them. One way to overcome this is for the developers to adopt co-learning while developing the system. The developers should give opportunities to users to give feedback and at the same time train the users on how to get the best out of the system. The user feedback would also help refine the program and fine-tune it to the user’s expectations. This way both the developers as well as users can learn from each other and this would be a big incentive for the users in their contribution to develop the AI system.
Consider the social dynamic.
One of the main issues facing the developers is to make the AI systems understand the context. This is very important as the context determines the type of conversation as well as how it will be conducted, and who will lead the conversation etc., Hence, in the initial stages AI-based systems should be part of the conversation where will observe how the conversation takes place, its interactions and gradually understand how and what type of conversations are likely and how to prompt or recommend actions to be taken. The users are free to accept or reject the recommendations and this acts as feedback to the AI systems about what questions can be asked in what context and help improve the program.
Support sustainable engagement.
In the initial stages, AI tools may be used just once or twice or rather sparingly by users and hence AI systems must deliver a very favourable outcome to the users to encourage them to use it more often. It is also necessary to design self-learning systems that can understand user requirements and adapt themselves to stay relevant to user needs.
All these factors need to be kept in mind when AI applications are developed to make them more relevant and user-friendly to ensure that it is adapted on a large scale;
The Demand for AI is Huge. The Hurdles to Widespread Adoption Are Even Bigger
By Ben Sherry
Inc 2022/12
R2G 