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TELUS International Survey Reveals Customer Concerns About Bias in Generative AI

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To supplement its existing capabilities in natural language processing (NLP), AI data solutions, computational linguistics, and content production, TELUS International introduces new generative AI solutions to reduce bias and hallucinations.

Customers are concerned about bias in AI algorithms and a perceived lack of transparency in the use of generative AI, according to a recent survey from TELUS International, a leading digital customer experience (CX) innovator with almost two decades of experience in artificial intelligence (AI).

Customers claim bias prevents AI from making smart recommendations and connecting them to new opportunities, leading to missed opportunities and irrelevant content.

  • More over half (55%) of respondents think bias in an AI algorithm led to the “wrong content” being delivered to them, including unrelated employment prospects and music they didn’t enjoy.
  • A third (32%) of respondents think prejudice in an AI system led them to lose out on a chance, such as getting their financial application approved or getting a career opportunity.

Generative AI opens up a new world of opportunities for businesses to improve the client experiences they provide, but in order for it to be successful, it must respond accurately and be devoid of harmful content. However, the tendency of generative AI to occasionally provide false or absurd information – a phenomena known as a hallucination – may have an adverse effect on hard-won client loyalty.

Only if brands are open and honest about how they’re using AI will consumers want brands to use it.

40% of American consumers, according to the report, don’t think platforms adopting generative AI technology are doing enough to shield users from prejudice and incorrect information. Additionally, more than 75% think that brands should be forced to audit their algorithms in order to reduce bias and prejudice before integrating generative AI into their platforms.

“With the rise of generative AI, the need for good and fair data has become more important than ever. Unlike traditional AI, generative AI creates new outputs based on the data it has been trained on, magnifying the impact of data quality on its overall performance”, “It is crucial that companies proactively address biased data and reckless algorithms from the start to avoid severe consequences and inaccurate outcomes. Model validation and tuning are essential for improving the performance and reliability of AI models as they help identify and address potential errors, improve accuracy and ensure that the model can effectively adapt to and make accurate predictions on new, previously unseen data. Additionally, by implementing appropriate policy guardrails, companies can protect customer data and promote a safer user experience while mitigating hallucinations and bias.”

Siobhan Hanna, managing director, AI Data Solutions, TELUS International

Human involvement

The significance of human participation was again emphasised by the respondents, with 49% saying that an AI program cannot function well without human input. Surprisingly, 19% of respondents said they were unaware that AI algorithms were reviewed by humans.

“Harnessing human intelligence in a manner that reduces bias is key to successful machine learning”, “Unlike AI, humans have the ability to understand context and tone, which is crucial to ensuring bias is responsibly mitigated. To effectively reduce bias in AI, companies must source trusted and diverse training data sets that incorporate a wide range of views and perspectives. By adopting a ‘human in the loop’ approach, companies can ensure increased accuracy and reduced bias in its AI datasets.”

Siobhan Hanna, managing director, AI Data Solutions, TELUS International

TELUS International can help you with your generative AI endeavours.

No matter where you are in the process of developing generative AI, TELUS International’s end-to-end solutions can help you move your efforts forward. Dataset engineering, the construction of training and test datasets, content generation and enhancement, model testing, and rapid generation and enhancement are just a few of the many AI solutions offered by TELUS International. The company offers wide capabilities for application development through the consultancy, design, build, deployment, and maintenance phases, as well as software engineering services to generative AI technology implementers.

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