Estimated read time: 3-4 minutes
Believe it or not, AI is everywhere.
Artificial intelligence is curating your Netflix recommendations and Instagram feed, answering the questions you lob at Siri or Alexa, and even helping drive your car.
In your work life, AI may be screening job applications, analyzing data or automating aspects of your business.
So if you think an AI strategy is one more thing you can outsource — "Hey, chat: build me a responsible AI plan" — it might be time to step back from the virtual assistants for a minute. AI is quickly becoming an invaluable tool, meaning every individual and business should have a plan for responsible AI use.
Before diving headfirst into AI use, here are some things to consider and why a responsible strategy is essential.
Why do I need an AI strategy?
Since AI isn't likely to go away anytime soon and is now factored into everyday interactions ranging from high school and college syllabuses to many business operations, everyone should have a basic understanding.
Artificial intelligence is generally defined as a computer system that can perform complex tasks usually done by humans — like reasoning, creating and problem solving.
According to NASA, one definition of AI is "an artificial system developed in computer software, physical hardware or other context that solves tasks requiring human-like perception, cognition, planning, learning, communication or physical action."
Some of the most commonly used AI in a typical person's life are speech and facial recognition systems (like on your iPhone), self-driving cars, digital assistants, chatbots like ChatGPT and image recognition programs.
Decide your core principles
Before evaluating proposed AI uses or deploying an AI governance framework, you'll need to decide on your core principles. Companies like Microsoft, IBM and Google all have similar versions of the following principles to guide their AI use.
- Fairness: Ensuring AI systems treat everyone equitably and avoid biases.
- Reliability and Safety: Building AI that performs consistently and safely, even in high-stakes situations.
- Privacy and Security: Prioritizing data privacy and keeping user information secure.
- Inclusiveness: Making sure AI technologies are accessible and work well for people from diverse backgrounds and abilities.
- Transparency: Being clear about how their AI systems work and which decisions they make.
- Accountability: Taking responsibility for the impact of their AI and putting governance processes in place to ensure responsible use.
Accountability: Taking responsibility for the impact of their AI and putting governance processes in place to ensure responsible use.
One of the best ways to avoid bias in AI is to ensure the people building it reflect a wide range of perspectives. A diverse team is more likely to catch blind spots and think through the ethical implications of AI decisions.
Prioritize transparency and privacy
You would probably be upset to find that a company was keeping or selling your data. So, it's important to prioritize transparency and privacy, in both your personal use of AI and your business needs.
AI does use massive amounts of data to draw conclusions and create out of seemingly thin air, so make sure you are following best practices such as anonymizing data, using encryption and being clear with customers if and how their data is being used.
Don't collect more data than you need — even if it's tempting to have as much information as possible.
Take the next step in AI leadership
Whether you're shaping AI strategy, navigating governance or simply looking to stay ahead in the evolving business landscape, the Salt Lake Chamber's Master Class: Building a Responsible AI Strategy, sponsored by Clarion AI Partners, will be held on March 27 and April 3 at the SLCC Conference Center's Miller Campus in Sandy, and can help you do just that.
Let lawyer-data scientist experts empower you with the knowledge and tools to effectively understand, govern, build and monitor AI in your organization. Reserve your spot today!
