A Framework for Measuring the Benefits of AI

Introduction 

Significant research has been invested in studying AI risks, a response to the rapid pace of deployment of highly capable AI models across a wide variety of use cases. Over the last year, governments around the world have established AI Safety institutes tasked with developing methodologies to assess the impact and probability of various AI risks. These range from existential threats, such as the potential ‘loss of control’ over AI systems, to more immediate concerns, including the perpetuation of historical systemic biases.

While the investment and research into AI risks are crucial (Trustible is proud to contribute to the US AI Safety Institute Consortium) focusing only on the potential harms is omitting the other side of the equation when it comes to AI ethics: benefits. The basis for many ethical decisions is that the benefits of using AI for a certain task outweigh the risks. However, you can only make that assessment if the potential benefits of an AI system are explicitly identified and quantified.

While several organizations, including NIST and MITRE, have started to create taxonomies and frameworks to categorize AI risks, we believe it is equally important to apply a similar structured approach to AI benefits. Developing a framework for AI benefits will help organizations conduct AI impact assessments, make more informed ethical decisions, and ensure that they are investing in AI capabilities that can yield measurable benefits for their organizations, users, and society at large. 

In this whitepaper, we outline our framework and taxonomy for measuring the benefits of AI. We include the stakeholder groups considered, the categories of benefits, and an initial list taxonomy labels along with proposed metrics for measuring each one. The goal of this blog post is to enable organizational AI leaders with practical guidance they can use to ethically justify the use of AI and measure their intended benefits. 

Stakeholders

Following our ethical AI framework, our benefits taxonomy focuses on 3 key stakeholder groups: People, Organizations, and Society.

People refers to individuals who benefit directly from an AI system. They may be the ‘user’ of the AI system, such as a student using AI to help them learn a new concept, or the ‘target’ of an AI system, such as when AI is used to help veterans fill out confusing insurance claims paperwork.

Organizations refers to businesses, non-profit groups, government agencies, or any other institution that develops or deploys AI. While individuals at these organizations may personally benefit, we typically think of benefits at this level as more abstract concepts such as increased productivity, improved reputation, or direct financial gains.

Society refers to communities, groups of people, and cultural elements. Societal AI benefits could include things like improved public health, reduced community violence, or improved safety of vulnerable populations. 

Categories of AI Benefits

In addition to identifying each type of beneficiary, we also identify different categories of benefits for each stakeholder group. We typically think of and measure benefits for each group and category differently.

PeopleOrganizationsSociety
Physical Health
Impacts to overall physical health of an individual
Financial
Impacts to key financial aspects of an organization including business costs and revenue
Justice
Impacts to crime, violence, and access to justice
Psychological
Emotional or mental impacts to an individual
Customer Satisfaction
Direct impacts to customer satisfaction outcomes
Public Health & Safety
Impacts to public health
Financial
Direct impacts to income or economic standing of an individual
Operational
Impacts to organizational efficiency or ability to scale
Environmental
Impacts to the environment
Privacy
Impacts to protection of personal information
Reputational
Direct impacts to the reputation of an organization
Opportunity
Impacts on access to economic, education, or other opportunities 
Freedom
Impacts to an individual’s freedom and autonomy
Legal
Direct impacts to an organization’s regulatory and civil liability or exposure
Community
Impacts to social interactions and shared experiences
Reputational
Impacts to an individual’s social standing, reputation, or dignity
ESG
Impacts to environmental, social, and governance factors of an organization
Culture
Impacts to key cultural traditions, norms, or values
Opportunity
Impacts to access to economic, educational, or other opportunities

Taxonomy

In our effort to help individuals and organizations develop a pragmatic approach to artificial intelligence, we have developed a comprehensive taxonomy of AI benefits. This taxonomy serves as a structured framework to systematically identify and measure the positive impacts that AI can have on various organizational processes and outcomes. By delineating clear categories and metrics, this taxonomy helps stakeholders understand the full spectrum of advantages AI can offer, facilitating informed decision-making and strategic investments in AI technologies.

NameDescriptionStakeholderBenefit Type
Reduced Task TimeReducing the time it takes an individual to perform a discrete task.PersonalFinancial
Reduced Task CostReducing the financial costs to an individual to perform a discrete task.PersonalFinancial
Increased ScalabilityEnabling a process to efficiently scale to additional users, sectors, or business units.OrganizationalOperational
Improved Task AccuracyIncreased accuracy or performance for a discrete task.OrganizationalCustomer Satisfaction
Product PersonalizationCustomization or personalization of a product/service that increases usability or user value.PersonalPsychological
Increased CreativityIncreased access to new ideas, or innovative ways of creating products/services.PersonalPsychological
Improved Knowledge DiscoveryEasier and more accurate access to information necessary to accomplish a task. OrganizationalOperational
Improved Customer RetentionIncreased probability that a customer continues to use a product/service.OrganizationalCustomer Satisfaction
Improved Physical HealthImproved physical health outcomes or information about bodily health.PersonalPhysical Health
Increased DiversityImproved diversity of communities or groups of people.SocietalCommunity
Increased InclusionIncreased acceptance of people with diverse backgrounds.SocietalCommunity
Improved Environmental SustainabilityImproved environment including lowered carbon emissions, reduced waste, or using recycled materials.SocietalEnvironmental
Repetitive Task AutomationAutomating highly inefficient repetitive tasks, particularly those that contribute to harmful bottlenecks or bloated bureaucracy.OrganizationalOperational
Reduced RiskReduction in potential for harm, especially potential legal harm.OrganizationalLegal
Improved LearningImproved educational outcomes or experiences including faster learning rates or academic achievements.PersonalOpportunity
Improved AccessibilityIncreased accessibility in society for people with disabilities.SocietalFreedom
Improved Organizational EfficiencyImprovements to overall operational efficiency, including helping facilitate cross team processes, reducing organizational friction, or reducing redundancies.OrganizationalOperational
Increased Product RevenueDirect increases in product/service revenues or contract growth rates over time.OrganizationalFinancial
Improved Public ReputationImproved social standing and reputation with core stakeholders.OrganizationalReputational
Increased Product SafetyImproved safety features, detection mechanisms, or failsafes.PersonalPhysical Health
Reduced Carbon EmissionsReduction in energy usage, water consumption, or direct carbon emission outputs.SocietalEnvironmental
Increased Access to EducationImproved access to educational services, institutions, or programs.SocietalEnvironmental
Reduced ViolenceReduction in criminal activities or physically harmful incidents.SocietalJustice
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