Trust is the key that unlocks successful and sustainable AI development. The AI visionary and Appian co-founder and CEO Matt Calkins has recently shone a bright light on this problem, calling on the AI industry to live up to the promise of trust that it is supposed to bring about by ‘ushering in a new generational shift in development that makes trust paramount’. It’s a bold call to action for AI that will certainly get the AI industry talking. Rather than viewing trust as a set of assurances that might be attached to an AI product after it has already been built, we see making AI trustworthy as the foundation upon which everything else should be built.
Even as AI systems are increasingly embedded in day-to-day life, it’s privacy, data integrity, and ethical use that have come to the fore. Calkins’ vocal criticism of the existing norms captures the vacuum of rules that address these issues. The solutions he proposes are a cutting-edge set of principles to help us build trust in AI development.
The concrete principles at the core of Calkins’s proposal included a commitment to the public disclosure of data sources, the humane management of private data, robust anonymisation of personal and intellectual property data, and strong consent protocols regarding personal and intellectual property data. This new regime, in other words, sets up the AI industry to protect its users’ right to privacy as much as it is a right governed by the commercial interests and political will of users themselves.
Whereas Calkins now sees compliance as only the beginning, the future must be built on trust: ‘This is the money the AI space wants to make,’ he adds. If you don’t like your current TV recommendations, just wait until you have an AI system that endlessly recommends things it knows you do not like. Even better, the future of the AI industry will have to tackle tougher problems than simply collecting and aggregating data. This must be the holy grail of AI: if you want your search to be really personalised, if you want real trust to become the currency in the AI space, you will have to be explicit about establishing that relationship. Suddenly, the game has opened up for developers to rebalance their approaches, realigning them more with users’ own expectations.
Appian, which has been voted a ‘vanguard’ of low-code automation solutions by analysts, is well-placed to profit from this conduciveness to trust. The company’s stance on ethical AI is a sign that it might be one of the leaders in a field in which ethical standards are coming to dominate increasingly. Its commitment to user data privacy and consent reflects a dedicated, trust-based model of AI development, creating a benefit with its partners and users concerning reliable AI.
The implications for Calkins’ project go way beyond Appian. Even as the AI industry is coming under greater scrutiny and pressure for regulation, the idea of a trust-based development model might be just what is needed to inspire the development of the AI industry in more sustainable and productive ways. The shift to demanding trust over data volume is one that will ultimately favour those who can develop powerful AI, but do so responsibly and transparently.
This historic moment in AI’s evolution demands that all AI practitioners, funders and advocates engage in a unified walk toward trust as the compass of technological development. What benefits could be garnered by adopting Calkins’ principles? A trust-based model suggests an avenue for reconciling technological innovation with the stakeholder’s interest in flourishing. The benefit in adopting this model is not a technological goal in itself, but the advancement of technology with the benefit of public support and trust.
As AI becomes increasingly suspect, this benefit to trust can’t be overstated. App’s idea is a critical example of the path forward for AI even as it continues to cause division: a future in which the default is a trust-based approach to users and a model of AI development that respects privacy and doesn’t exploit users but seeks their informed consent. Appian’s model makes clear the clear benefits of trust, if the AI industry follows its lead. AI development will be more innovative and useful if the imperative toward trust gains traction, for the benefits to both individuals and society will also become more evident. Computing is changing, and the growing imperative toward trust is a signal that it’s changing in ways more responsible than those that have fueled the deeply dark side of AI.
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