Building Trust in AI

Artificial Intelligence (AI) is not the future; it is already here. It is in your pocket, car, television, shopping experiences, and more and more in the automated workflows for businesses. But even as AI is becoming more prevalent, some people are still wary of the technology. Companies still have a lot to do in building trust in AI. At Squark, we believe AI should not be a black box. Not only have we simplified the process of data science leveraging AI, but we’ve set out to make it transparent, explainable, and trustworthy.

How Many People Trust AI?

According to a survey published in January 2022 by Ipsos for the World Economic Forum, 60% agree that AI products and services will make their lives easier. 60% also expect AI to profoundly change their daily lives in the next 3-5 years. However, just 50% say that they trust AI companies as much as other companies. And 40% say that AI-powered products and services make them nervous. The results vary across geographies and demographics, but the bottom line is that there is still a lot of work to do to build consumer trust in AI.

Building an AI Solution that Customers Can Trust

“In order to trust artificial intelligence, people must know and understand exactly what AI is, what it’s doing, and its impact,” said Kay Firth-Butterfield, Head of Artificial Intelligence and Machine Learning at the World Economic Forum. “Leaders and companies must make transparent and trustworthy AI a priority as they implement this technology.

Here are just a few ways Squark is working to make our AI transparent and trustworthy: 

1. Leading Data Models and Algorithms: Squark stays on top of the most up-to-date models, features, and techniques, so you don’t have to. Squark provides the algorithms and the resultant model metrics for all of your projects to understand the model’s detailed performance.
2. Accuracy: Every time you execute a project on Squark, whether for the first time or re-running a model with new data, thousands of models are run to ensure that the best one is selected for your specific data. Fully validated and cross-validated results, as well as other details, are provided.
3. Security: Security is at the core of Squark. Squark takes every precaution and follows all relevant regulations.
4. Scalability: Squark’s SaaS is more scalable than platforms that require complex integrations and engineering services at a fraction of the cost. There is no limit to the data that can be loaded into Squark.
5. Bias and Fairness: Address bias and create ethical AI models. The largest source of bias in an AI system is the training data. Understanding how to measure bias enables opportunities to mitigate issues of bias.
6. Explainability: Squark’s Explainable AI goes beyond traditional attribution and contribution analysis approaches to understand why AI models and predictions are generated.

Providing these elements is just the start of building trust in AI. Squark is constantly evolving our product development and customer relationships to make sure that our customers have confidence in the results so they can take those and impact their businesses. For additional information about AI, check out our resource library and blog.

Interested in learning more about Squark’s trustworthy AI? Schedule a demo.