30. JUNE 2022 Responsible AI And How to Harness It to Power Sustainable Action

Responsible AI Ensures Value Creation from Data in a Responsible and Sustainable Manner

The debate about autonomous driving is a prime example of how artificial intelligence (AI) can spark hopes and fears. Self-driving cars have the potential to speed up traffic and unburden drivers. Yet a study by car manufacturer Audi revealed that 41% of all global respondents are suspicious of autonomous vehicles, and 38% are fearful. AI leaders face the challenge of convincing both employees and the public of the far-reaching benefits of artificial intelligence.

Companies that use AI to improve their processes have the power to inform and educate both sides. They can engender trust by laying their cards on the table and being completely open about their experiences with AI. The solution: Responsible AI.

Responsible AI is the practice of developing and deploying AI systems with good intentions in a responsible manner, helping to empower employees, business, and society. Central to this are the core principles of transparency, fairness, and the ability to make the technology easily understandable.

The key elements of Responsible AI according to Gartner®:

  • Trust in the creation of corporate and social added value
  • Fairness and explainability through transparency to avoid bias
  • Responsibility and compliance with legal regulations

On the one hand, compliance with these principles creates positive added value for society; on the other hand, values such as transparency ensure that solutions are better accepted by employees.

The term Responsible AI also incorporates:

  • AI Ethics (ensuring ethical behavior when using artificial intelligence)
  • Green AI and Sustainable AI (consideration of environmental impact and carbon footprint when using artificial intelligence)
  • Explainable AI (making the workings of a model clear to a specific audience).

Companies can ensure that AI is implemented responsibly by adhering to models of AI governance, including TRiSM or AI Ethics. When creating and implementing our data products, ONE LOGIC follows the principles of the international research and consulting firm Gartner® and emphasizes fairness, transparency, security, and social value.

AI TRiSM and AI Ethics are cornerstones of Responsible AI

Data Science and AI Leaders are aware that the use of artificial intelligence may pose risks. These can include privacy violations when personal data is used or if an autonomous system makes critical decisions during an accident. According to Gartner®, analytics leaders pursuing Responsible AI need to meet certain criteria—most notably Trust, Risk, and Security Management (TRiSM). In this way, risk can be proactively managed before problems arise.

“The AI TRiSM market comprises multiple segments necessary to manage new risks and threats introduced by AI.”

– Gartner®

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner® document is available upon request from Gartner®.

At ONE LOGIC, our data products empower customers to use AI as a tool to make better decisions based on data.


This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from [https://www.gartner.com/document/3947359?ref=solrAll&refval=326672644]

ONE LOGIC uses data products responsibly

Our AI principles are built on a foundation of responsibility. The ethical and sustainable use of data is therefore deeply rooted in our corporate mission and vision.

Our vision is to reveal the truth behind data and the profitable value that can be derived from it. When implemented responsibly, AI can benefit people in many ways, such as by easing the burdens of manual tasks.

Our mission is to develop innovative data products that transform data into sustainable value, by, for example, making processes more efficient and reducing the resources consumed.

Our many customer projects have already demonstrated how artificial intelligence can be implemented to generate tangible and positive value.

Avoiding animal testing in the cosmetics industry

Animal testing is a particularly controversial topic and many people do not believe that the use of animals in research can be ethically or morally justified. We worked with a customer in the cosmetics industry to address the problem and helped them find a viable alternative to animal testing.

Problem

  • For newly developed cosmetic ingredients, a potential skin reaction must be assessed without animal testing.
  • (Laboratory-based) tests already exist, but they are not accurate enough.
  • Regulations set by science, regulatory authorities, and companies must all be complied with.
  • Only an extremely small data set with a high proportion of categorical data is available.

Solution

  • Identify testing methods that complement each other to allow advanced methods to be used in research.
  • Create a sensitization prediction algorithm with 25% greater accuracy over single test procedures or animal testing.

Sustainability with AI

In another project, ONE LOGIC was able to demonstrate how the use of AI improves logistics and helps conserve resources. Read the full article here to learn how logistics efficiency allows the same volume of goods to be shipped with up to 40% fewer truck trips, thereby significantly reducing CO2 emissions. This project clearly shows that artificial intelligence can help meet sustainability goals.

Responsible AI—the cornerstone of sustainable and ethical projects

Artificial intelligence is already transforming the world and raising important questions for societies and economies. The responsible use of AI should be on every data scientist and AI leader’s radar. Responsible AI—including AI Ethics and Green AI—is the cornerstone of successful, sustainable, and ethical projects.

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Disclaimer:

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
Gartner, Market Guide for AI Trust, Risk and Security Management, 1 September 2021, Avivah Litan, et. Al.
Gartner, Expert Insight Video: What Is Responsible AI and Why You Should Care About It? 10 November 2021, Svetlana Sicular
Gartner, AI Ethics: Use 5 Common Guidelines as Your Starting Point, refreshed: 31 December 2020, Published 11 July 2019, Frank Buytendijk,et. Al.
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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