How Can Organizations Build a Robust Framework for Responsible AI?
If 2023 was the year of AI discovery, 2024 is the year AI is being put to work. The latest McKinsey Global Survey on AI revealed that 65% of respondents—nearly double the number reported just ten months earlier—regularly use generative AI. Artificial intelligence offers potential improvements in various business areas, including increased efficiency through reduced manual tasks and enhanced data-driven decision-making. AI can also improve the customer experience by providing enhanced personalization and accessible services outside business hours.
However, even as some businesses recognize the cost savings associated with AI, the risks can be challenging to understand and manage. Many organizations need more training and skills to implement AI effectively. Software and technical tools can be a barrier when legacy systems prevent the seamless integration of new technologies. Perhaps most importantly, poor-quality data can lead to incorrect conclusions and significant errors. Responsible adoption requires developing practices that allow you to benefit from AI while addressing its inherent risks. This includes deploying AI solutions in ways that align with ethical principles and legal standards. The following steps can help you build a robust framework for responsible AI.
Determine Your AI Readiness
While business leaders worldwide recognize the importance of investing in AI technology, a Lenovo survey revealed that most believe their computing infrastructure and corporate policies on ethical use are not "AI-ready." Legacy systems often rely on outdated technology, making them incompatible with AI solutions. Companies with tight IT budgets may delay updating systems needed to integrate AI. Even with successful integration, legacy systems can still present increased vulnerabilities in data privacy and cybersecurity.
Ethics policies regarding AI use are also uncharted territory for many, with numerous potential dangers. AI can potentially create unintentional biases and data misuse, violating legal regulations and damaging a business's reputation.
Governments have begun establishing regulatory requirements around AI in response to its rapid growth and the potential for severe misuse. In 2021, the European Union produced the first-ever dedicated law on AI use. The EU AI Act ensures that AI systems are safe, transparent, traceable, non-discriminatory, and environmentally friendly. It also mandates human oversight of these systems to prevent harmful outcomes.
As AI use grows, other governments will likely adopt similar regulations. To maintain legal compliance, you'll need to stay updated on the rapidly changing regulatory environment and ensure your teams create and update internal policies accordingly.
Establish a Multidisciplinary Team
The introduction of AI will impact every department in your organization. Developing an adequate understanding of—and effective use protocols of—the technology requires input from experts across various fields, including ethics, legal, data science, and risk management. By creating a collaborative environment, businesses can address more potential concerns and advantages with a common language and all the data to make informed decisions.
As new regulations take effect, international companies must comply with data privacy and cybersecurity regulations in different parts of the world. Organizations will also need to consider the impact of AI use on employees and the necessary training programs to provide employees with AI skills. Forming a team prepared to address all these challenges will assist in the seamless adoption of AI use in your organization.
Always Use Quality Data
Any AI solution is only as good as the data that trained it. AI relies on substantial amounts of input data, which it uses to generate outputs. However, poor data input results in poor data output. While minor issues might only lead to poor spelling or grammar, insufficient data can have far more severe consequences, including inaccurate data and biased outcomes that can negatively impact users and customers.
When programming reflects the subjective attitudes of its trainers or input data, it produces biased algorithms. These biased algorithms can drive discrimination, often creating significant disadvantages for underrepresented groups. Inaccurate data creates equally concerning scenarios. If an AI reproduces incorrect data as facts, these “facts” can be relied upon and spread by humans and other digital systems, potentially causing harm.
Consider Cybersecurity Concerns
Many high-quality AI systems perform tasks as intended, but generative AI technology can suffer from flaws related to corrupt data and poor comprehension. AI systems can sometimes process information poorly and present incorrect statements as facts. These flaws, known hallucinations, can even include fabricated sources.
AI is not designed to perform malicious tasks, but systems can be tricked into providing sensitive information when questions are posed in specific ways.
Hackers can manipulate the data used to train AI models, intentionally corrupting systems to achieve specific outcomes or provoke reactions. These data poisoning attacks can create security vulnerabilities or biases that produce undesirable results.
To avoid such issues, businesses must establish guidelines to ensure secure AI model development. The Guidelines for Secure AI System Development, created by the National Cyber Security Centre, the Cybersecurity and Infrastructure Security Agency (CISA), and agencies from 17 other countries, help organizations deliver secure outcomes when developing and deploying AI systems.
Use Tech-Powered Tools With Human-Centered Decisions
AI-powered systems are advanced tools that can reduce manual workloads, improve efficiency, and minimize errors. However, these tools still require well-trained, knowledgeable, and engaged people to train them.
While technology can solve complex problems, it cannot replace the human thought process. Human oversight and intervention will always be necessary for the responsible use of AI. These interventions include:
Setting responsible boundaries for AI use
Providing quality training to ensure accurate results
Continually refining AI systems to align with corporate and societal values
Ignoring the growth of AI in business is no longer an option. As more businesses adopt AI technology and refine its usage to mitigate potential risks, such tools will become essential to stay competitive. By understanding the risks and adopting responsible policies, you can scale your solutions for greater success.
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Don't rely solely on AI technology to drive your globalization efforts as you expand your business. At Vistatec, we have deep experience communicating our customers' content, services, and products in a clear and engaging language that reflects local insights, linguistic nuances, and cultural differences. Contact us to learn more about our global content solutions.
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