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How to build trust in AI


A few years back, IT experts and leaders predicted that AI is going to be a major part of our futures, and today, it is here in our living rooms, cars, in our pockets. It is a part of our daily lives and its influence would continue to affect our lifestyles in the coming years. As the technological advancements and innovations have continued to expand their roles in our lives, we have started wondering what level of trust we can place in these AI systems and how AI development companies can build trust in AI solutions? 

When it comes to technology implementation, especially AI, the industry operates on the €œno trust; no use€ assumption. Tech companies and AI experts are coerced about how to build trust in AI solutions to foster quick adoption across the industries. 

There are three main pillars that AI experts and tech companies need to focus on while they are trying to build trust for the solutions: 

  1. Performance: One should focus on if the solution is built correctly according to the requirements. Is it safe and will it perform its functions well?
  2. Process: Does the solution perform the way we intended? Can the outcome be predicted with the help of the solution?
  3. Purpose: Does the solution serve the purpose? Does it adhere to ethical standards?

Since the outbreak of the global pandemic, we have witnessed how AI has helped in transforming almost every industry beginning from healthcare to logistics but along with the transformation, it has also brought questionable implications on the table with itself. 

Consumers expect the freedom of choice at their disposal and tech experts need to figure out ways to make consumers want to explore these AI solutions by themselves rather than forcing them to adopt them. Similar is the case when it comes to implementing AI solutions across organizations. The management often applies a bottom-up approach while implementing such solutions across their organization to make the employees understand the importance of these technological advancements rather than applying top-down decisions. Through this approach, organizations aim to have the majority of the employees on board and work collaboratively towards their visions and goals. 

One of the key concerns right now is to change the way organizations and consumers talk about AI solutions. Tech experts & AI enthusiasts have to focus on the tone of the conversation about AI. They should continuously focus on why it is important to build a new and personal relationship with AI solutions rather than just discussing the hype, threats, and fears they come along with. When organizations understand the importance of these advanced AI solutions and how they can be beneficial in the long run, they can build a new level of trust. 

Building trust in AI solutions would require a significant amount of effort from tech companies and AI experts to instill in it a sense of morality, operate in full transparency, and provide education/information about the opportunities these solutions will create for the businesses and consumers. 

Tech leaders and experts understand that transparency is the key here. To trust these solutions, organizations need to understand how an AI system arrives at its conclusions and recommendations. We need this sort of transparency in all the areas in which AI will be used which would help the tech companies gain a significant level of organizations and consumers in the technology. Another effective way to provide transparency is through educating the prospects about the misconceptions, AI€™s abilities, etc. Moreover, a lack of clarity over which jobs AI might impact breeds an additional level of distrust in the technology solutions, thus, it is important to educate organizations and leaders about the touchpoints where the disruptions might occur and how they can be managed with the help of these solutions and further teach them the skills required to perform new jobs which will be created with the implementation of these advanced solutions. 

Just as trust needs to be built in our personal and business relationships, it is equally important to build trust between an AI user and system. Implementation of such transformative technologies would only be successful if there is a clear understanding of the methods and benchmarks amongst different stakeholders. 

Furthermore, to get the desired results, along with transparency and education, IT leaders and AI development companies must focus on removing the barriers to AI adoption. With the built trust, organizations will gain confidence while implementing these solutions. 

It is very much clear that unless we have organizations and consumers trusting AI solutions, we will have a tough time solving the pain points of businesses. We have already seen how AI is helping organizations tackle unforeseen problems during the pandemic. We need to continue getting our AI systems to interact with humans (organizations & consumers) to ensure that there comes a time when we trust AI systems equally as compared to trusting human capabilities.