Trustworthy & Responsible AI is Everyone’s Business

The proliferation of AI is happening everywhere and to all of us. It is a powerful technology that we can use to analyze data, optimize processes, and generate personalized content. But as they say: with great power comes great responsibility, and trustworthy and responsible use of AI is something we all must take seriously.

Research from IBM¹ shows that 2024 will be the year when business leaders need to balance technology and trust. Of course, building trust in every aspect of an organization is not a new concept. But it has become more challenging with generative AI and other global factors.

AI can be used to cut costs and increase your ROI, but we need to do it responsibly and ethically. Trustworthy and responsible AI is about building and using AI systems in a way that maintains trust, respects people’s integrity, and is aligned with ethical principles and social values. Neglecting to employ AI in a trustworthy and responsible manner may cause biased decision-making and promote inequalities within society.

- From a business perspective, failing to prioritize responsible AI practices exposes you to legal and reputational risks, but it also undermines consumer trust, and may have a negative effect on the brand and long-term viability in the market, says Tahira Naeem, Senior AI Business Developer.

Easy to Use - Harder to Quality Assure

AI is easy to use, pre-built models are available online, and anyone can start their first AI project on a laptop in an afternoon. However, the difficulty lies in ensuring the quality of the data and results. You as a business have a responsibility to provide receipt of what model you use and what data it has been trained on.

- Plenty of models use data that is gathered online, and we all know how unreliable the internet is. Go ahead and ask DALL-E to generate an image of a successful CEO and you will instantly uncover the bias of the model.

Models for generative AI are programmed to always to give an output. That means that when an AI model does not have access to the data it needs it makes things up - it “hallucinates.”

- You need to have a governance model for quality control. Humans often need to add an analysis layer before making decisions based on AI-generated results.

Examples of Use Cases that Call for Caution

It may be effective to use AI to analyze resumes and assess candidates' qualifications and suitability for a position. However, it is important to ensure that the algorithms are impartial and do not discriminate against candidates based on gender, age, religion, or ethnic background. The more that is at stake, such as costing an individual an opportunity, the more stringent the control needs to be.

When using AI in marketing, for example to create personalized offers, it is important to be transparent with customers about how their data is used and to give them the option to opt out if they wish. It is also crucial to respect customer privacy and adhere to data protection laws and guidelines.

Keys to trustworthy and responsible AI

• Allow the generative AI model to assist you but maintain human oversight and decision-making authority.

• Establish a robust governance framework to guide AI usage.

• Foster transparency within organizations regarding AI usage and encourage feedback from users and stakeholders.

• Promote ethical awareness among AI developers and users, emphasizing the ethical implications of their decisions and actions.

• Select appropriate AI models and ensure they are trained on relevant and ethical data sources.

[1] Turning data into value: How top Chief Data Officers deliver outsize results while spending less. IBM Institute for Business Value. March 2023. https://ibm.co/c-suite-study-cdo.

Tahira Naeem

Senior AI Business Developer

Arrow

More articles

Use AI to Solve Real Problems

Cost cutting is often at the top of the list of desired outcomes of an AI implementation. But a better way to achieve a successful application of the technology is to identify and address real business problems. Companies that can monetize their organizational data will gain nearly double the ROI from their AI capabilities than their peers.

Read the full article

Test AI in the lab

AI has turned a lot that we knew about business development on its head, and we’re all trying to orient ourselves in this paradigm shift. Do you want to level up your knowledge and be an IT-partner who can guide your customers on their AI journey? Arrow welcomes you to join them in the AI lab to learn and explore

Read the full article

Top 5 AI Must Knows

Do you remember when all businesses wanted an app? And that too many started designing and building a solution without making sure that it would be relevant to the customer experience. Now many businesses risk falling into the same trap with generative AI. Pay attention to these 5 must-knows for a smoother AI journey.

Read the full article

Understand the value of AI. Try it out in our lab

Book a time at our lab

Sponsor

About Arrow

Arrow ECS is a technology enablement company that delivers innovative IT solutions to solve complex business challenges in the market. We offer value-added distribution, business consulting and services to leading technology manufacturers and their channel partners.