FICO Survey Finds 65% Of Respondents Don't Understand How AI Model Decisions or Predictions Are Made
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FICO Survey Finds 65% Of Respondents Don’t Understand How AI Model Decisions or Predictions Are Made

FICO, a global analytics software firm, has released its State of Responsible AI from market intelligence firm Corinium which found that despite the increased demand and use of AI tools, almost two-thirds (65%) of respondents’ companies can’t explain how specific AI model decisions or predictions are made. The study found that the lack of awareness of how AI is being used and whether it’s being used responsibly is concerning as 39% of board members and 33% of executive teams have an incomplete understanding of AI ethics.

Conducted by Corinium and sponsored by FICO, the report – State of Responsible AI – surveyed 100 C-level analytic and data executives and conducted in-depth interviews with industry thought leaders from MIT, AI Truth, The Alan Turing Institute, World Economic Forum, and FinRegLab to understand how organisations are deploying AI capabilities and whether they are ensuring AI is used ethically, transparently, securely and in their customers’ best interests.

While compliance staff (80%) and IT and data analytics team (70%) have the highest awareness of AI ethics and responsible AI within organisations, understanding across organisations remains patchy. As a result, there are significant challenges to build support to establish practices as the majority of respondents (73%) have struggled to get executive support for prioritising AI ethics and responsible AI practices.

“Over the past 15 months, more and more businesses have been investing in AI tools, but have not elevated the importance of AI governance and responsible AI to the boardroom level,” said Scott Zoldi, Chief Analytics Officer at FICO. “Organisations are increasingly leveraging AI to automate key processes that – in some cases – are making life-altering decisions for their customers and stakeholders. Senior leadership and boards must understand and enforce auditable, immutable AI model governance and product model monitoring to ensure that the decisions are accountable, fair, transparent, and responsible.”

Whose Responsibility is it?

The study found that almost half (49%) of the respondents report an increase in resources allocated to AI projects over the past 12 months, followed by team productivity (46%) and predictive power of AI models (41%). Whereas, only 39% have prioritised increased resources to AI governance during model development and 28% have prioritised ongoing AI model monitoring and maintenance.

Despite the embrace of AI, what is driving the lack of awareness? The study showed that there is no consensus among executives about what a company’s responsibilities should be when it comes to AI.

The majority of respondents (55%) agree that AI systems for data ingestion must meet basic ethical standards and that systems used for back-office operations must also be explainable. But this may partly reflect the challenges of getting staff to use new technologies, as much as wider ethical considerations.

More troublesome is that almost half (43%) of respondents say they have no responsibilities beyond meeting regulatory compliance to ethically manage AI systems whose decisions may indirectly affect people’s livelihoods – i.e. audience segmentation models, facial recognition models, recommendation systems.

“AI will only become more pervasive within the digital economy as enterprises integrate it at the operational level across their businesses,” said Cortnie Abercrombie, Founder and CEO, AI Truth. “Key stakeholders, such as senior decision makers, board members, customers, etc.; need to have a clear understanding on how AI is being used within their business, the potential risks involved and the systems put in place to help govern and monitor it. AI developers can play a major role in helping educate key stakeholders by inviting them to the vetting process of AI models.”

Combating AI Bias

What can businesses do to help turn the tide? Combating AI model bias is an essential first step, but many enterprises haven’t fully operationalised this effectively as 80% of AI-focused executives are struggling to establish processes that ensure responsible AI use.

Currently, only a fifth of respondents (20%) actively monitor their models in production for fairness and ethics, while less than a quarter (22%) say their organisation has an AI ethics board to consider questions on AI ethics and fairness. One in three (33%) have a model validation team to assess newly developed models and only 38% say they have data bias mitigation steps built into model development processes.

However, evaluating the fairness of model outcomes is the most popular safeguard in the business community today, with 59% of respondents saying they do this to detect model bias. Additionally, 55% say they isolate and assess latent model features for bias and half (50%) say they have a codified mathematical definition for data bias and actively check for bias in unstructured data sources.

Businesses recognise that things need to change, as the overwhelming majority (90%) agree that inefficient processes for model monitoring represent a barrier to AI adoption. Thankfully, almost two-thirds (63%) of respondents believe that AI ethics and responsible AI will become a core element of their organisation’s strategy within two years.

Educating key stakeholder groups about the risks associated with AI as well as the importance of complying with AI regulation are two critical steps to addressing companies blindspots around responsible AI. Additionally, the report highlights several best practices that will help organisations plot a path to responsible AI, including:

  • Establishing practices that protect the business against reputational threats from irresponsible AI use.
  • Balancing the need to be responsible with the need to bring new innovations to market quickly.
  • Securing executive support for prioritising AI ethics and responsible AI practices.
  • Futureproofing company policies in anticipation of stricter regulations around AI.
  • Securing the necessary resources to ensure AI systems are developed and managed responsibly.

“The business community is committed to driving transformation through AI-powered automation. However, senior leaders and boards need to be aware of the risks associated with the technology and the best practices to proactively mitigate them. AI has the power to transform the world, but as the popular saying goes – with great power, comes great responsibility,” added Zoldi.

Author

  • Francis is a junior journalist with a BA in Classical Civilization, he has a specialist interest in North and South America.

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