By Samuel Bousfield, Data Consultant, Altis Consulting
What is AI
AI refers to machines and systems that can perform tasks that have traditionally relied on human intelligence, such as understanding language or recognising patterns. A major development in AI today is Large Language Models (LLMs), which have been trained on massive amounts of textual data, and are designed to generate human-like responses, answering questions in a textual format. LLMs are a subset of Generative AI, which in general is designed to generate content that mimics human creativity, and includes models that are not LLMs, such as DALL-E, which is designed to generate image content. Generative AI is a subset of AI typically based on Machine Learning (ML) techniques, which allow the model to learn from data for the purpose of improving performance over time, like humans. Not all ML models are designed for, or used in, Generative AI. The distinction is a little complex, but in general terms, ML is used for predictive and analytical purposes, and Generative AI is used in the creation of “new” and “original” content.
Unlock Business Potential
Building Trust with Customers
Fundamentally, trust is the key asset for any business, and there are countless examples of how a misuse of trust has damaged a company. It is therefore important for companies to keep customer trust in mind when developing new methodologies and adopting new technologies. A core Australian value is to give everyone a “fair go”. Australian customers are more likely to feel confident in a service, product or business powered by AI systems that are designed and proven to be secure, accountable and fair. While many customers are justifiably excited for AI, seeing the very real benefits, many customers are also justifiably viewing AI with increasing scrutiny, seeing the very real problems. Trust can be built with both of these groups, simply by ensuring AI systems are accurate, beneficial, understandable, accountable, and auditable.
Avoid Legal and Regulatory Risks
The other area where AI technologies are facing increasing scrutiny is in the legal and regulatory sphere. Businesses must ensure their systems comply with ever-evolving legal and regulatory frameworks. Implementing ethical AI practices can help business avoid risks like biased decision-making or violations of privacy laws. Adhering to strict ethical guidelines and governance frameworks, and ensuring transparency in AI operations, businesses can avoid repercussions by staying ahead of government regulations.
Gain a Competitive Edge
Innovation is essential for any business that aims to succeed. Without innovation, businesses risk stagnation, and stagnation isn’t about staying the same – it’s about being left behind as the market landscape evolves.
AI plays a pivotal role in fuelling future innovations, by enabling businesses to harness vast amounts of data from diverse sources. Through advanced analysis and interpretation, AI uncovers valuable insights that would otherwise remain hidden, allowing companies to continually innovate and adapt. In this context, innovation and adaptation do not necessarily mean market disruptions but can be as subtle as integration into business processes to allow for optimisation of operations or supply chains, enhancing market strategies, and personalising customer experiences. This enables businesses not only to improve their offerings but also ensures businesses can stay ahead of the curve in a rapidly changing market.
Furthermore, the responsible use of AI communicates to customers that a business is not just keeping up with market trends but is actively involved in shaping their future. In many cases, AI-driven innovations, such as market basket algorithms, work behind the scenes to subtly enhance the customer experience – subconsciously proving that a business is investing in the appropriate technologies to anticipate and meet customer needs.
Responsible and Effective AI
Ethics by Design
Ethics by Design is about ensuring AI systems are developed and used responsibly, with respect for the humans who use and humans who are affected by the AI systems by design. When developing the business case in how, why and where AI systems are to be integrated into business processes, ethical issues, such as fairness, privacy and bias must be considered. While ethical considerations will vary by organisation and business process, an example is that AI used in hiring decisions must not unfairly favour or disadvantage certain groups on certain characteristics, such as race or gender, unless these characteristics are relevant.
Transparency by Design
Transparency by Design means making AI systems understandable to the users. This means clear explanations of how models reach their relevant outputs, clearly communicating the data, assumptions and any embedded biases, ensuring operations are open and accountable. For businesses, this is fundamental to enabling the use of AI, allowing users, subjects and regulators to understand how and why an AI provides its outputs. This is fundamental to building trust with customers by ensuring that they can find out how they are affected by AI, avoiding legal and regulatory risks by ensuring that businesses can discover where AI is at risk of violating legal and regulatory standards and easily implementing fixes, and gaining a competitive edge by identifying where the AI is not performing as expected.
Prioritise Data and Security
AI relies on data, so ensuring that data is accurate, clean, available and secure is paramount. Businesses are required to implement strong data protection measures and comply with appropriate data regulations. Prioritising data and data security is the key value behind implementing proper data governance frameworks.
Adopt Data and AI Governance Frameworks
Robust governance frameworks are essential in managing AI and data in structured and compliant ways. By adopting appropriate and clear data and AI governance policies based on industry best practices, businesses ensure that data is used responsibly and in accordance with regulations. These frameworks also help to provide transparency and accountability in AI operations to the internal users of the AI systems, ensuring the human support of the AI system is proceeding via the correct roles, responsibilities and decision-making processes.
Encourage Data Literacy
For AI to be truly effective, all users should have a basic understanding of data and AI. Encouraging data literacy within your organisation will foster a culture where AI is used effectively, responsibly and appropriately. Educated teams of Subject Matter Experts are best positioned to understand how AI decisions are made, interpret AI outputs, and just as importantly, identify where AI can be improved, or in some cases, where AI is just plain wrong.
Audit and Monitor AI Outputs
Appropriate use of AI systems are not “set and forget” solutions. Regular auditing and monitoring of AI outputs are critical to ensure that models perform appropriately and as expected. This helps the quick identification and addressing of issues, such as bias, inaccuracies or unexpected behaviours, ensuring that the AI system is properly aligned with business objectives, ethical standards and regulatory requirements.
Conclusion
Artificial Intelligence promises a revolution in business practices, offering powerful tools for enhancing all aspects of the product lifecycle. However, the effective and responsible integration of AI requires a strong understanding of its capabilities (and incapabilities) and a commitment to ethical practices. By educating all employees, not just the ‘data’ team, adopting appropriate governance frameworks and ongoing auditing of AI outputs, business can maximise the benefits of AI, while minimising the risks.
Ultimately the key to success in applying AI rests in maintaining the trust of the humans who use and are affected by the system, staying compliant with regulation and embracing innovation. Critically, AI systems and the decisions made based on their outputs, need to be accountable. Australia doesn’t need a second robodebt debacle. Businesses that stay ahead of the curve will gain a competitive edge in their products and services, and position themselves for long-term success, as responsible, and forward-thinking leaders in their industry.
At Altis, we provide expert advisory and delivery services in Artificial Intelligence and Machine Learning. Contact us via the website or connect with us on LinkedIn to explore the best solution for your business.