From the moment we wake up to the moment we hit the bed, AI ( Artificial Intelligence) plays an irreplaceable role in our daily lives. It’s there in your TV, remote, car, office- you name it, AI owns it! You’ve probably spoken to it multiple times daily without even realizing it. “ Alexa, play my favorite music track,” or “Hey Siri, what’s the weather out there?” – These are simple instances that make us realize how quickly AI has integrated into our everyday lives.
The invisible presence of AI in our daily lives makes things a lot easier than it was. It helps you finish an email quickly, set timers to wake you up, and even populate the Netflix recommendations for the weekend. As artificial intelligence continues to evolve at breakneck speed, so do the fears and concerns surrounding its usage. From the unsettling prospects of biased decision-making to the looming threat of job displacement, society does look at AI with a skeptical eye.
However, what sparks controversy the most is the fear of AI failures and the costly impacts resulting from them. One of the best examples of this is the Boeing 737 Max jet that allegedly nosedived due to a malfunctioning safety system.
Find the Delicate Balance Between Power & Responsibility
AI’s potential is undoubtedly vast. Right from helping to battle the COVID-19 pandemic to helping you find that one photograph you are looking for from the sea of pictures stored in your smartphone, AI is now a necessity and not just an option.
But, great power always comes with greater responsibility. Hence, it is only imperative that we find ways to harness the power of AI while finding ways to mitigate the risks and failures.
At the heart of this challenge lies the close relationship between the users and AI. The key to success in this scenario is- rooting AI in human needs. As long as we prioritize the ethical and social consequences of AI development and deployment, we can ensure that this remarkable technology benefits society.
“AI is only a tool; The choice about how it gets deployed is ours”
Oren Etzioni
Human-Centered Responsible AI- Prioritization of Humans Over Machines
So, how do we ensure that AI can be used in such a way that it prioritizes human well-being, values, and ethics? The answer is human-centered responsible AI. It recognizes that AI is not just a neutral force and accepts that the choices we make regarding its deployment and development can have far-reaching consequences on society as a whole.
While some may argue that an autonomous approach to AI can promise a world free of human errors and bias, the human-centered approach begs to differ. It recognizes the ultimate truth that machines can never replace the vast spectrum of human creativity and intelligence. Rather than allowing algorithms to control our lives, we should take the driver’s seat and direct the solutions that will help AI to enhance and complement our lives.
When AI is plagued by poor decision-making, bias, and errors, it can erode trust and do more harm than good. This is why we need a human-centered AI that prioritizes user experience. The creation of effective, ethical AI tools requires aligning what’s technically feasible with what’s feasible for the business. So, what are the 3 rules to achieve this delicate balance?
- Understanding human experience and designing AI tools with people’s values, ethics, and needs in mind.
- Being transparent about how decisions are made and how AI will be used.
- Being prepared to make corrections in case of unintended consequences or results.
The Best Practices for Human-Centered Responsible Artificial Intelligence
Fix the Problem, Assess the Needs
A mistake we often make is that we create the technology first and then find its use later. Instead, here we should design and create a technology that fixes a current real-world problem. The key is to start from the customer’s needs and work backward. Let’s take the example of real-time call transcription in the emergency services sector. We can utilize AI to flag the key information in 911 calls. While AI collects vital information, such as the caller’s location and type of emergency, responders can focus on talking to the caller, calming them down, and helping them address the problem.
Create Clarity, Remove Ambiguity
Effective communication is the key when it comes to using AI. The design of AI tools should ensure that they are able to present information in an easily understandable manner. AI tools should also be able to express doubts and uncertainties. For instance, an AI-powered transcription tool can be designed in such a way that the tool adjusts the font of transcription to indicate that AI is uncertain about a particular word. This will help users to note these words and make better-informed decisions. In the end, AI tools will become more effective when they become familiar with their users and their needs.
Stay Human-Focused, Prevent Disasters
Tailoring AI design to fit seamlessly into existing workflows and solve specific problems can deliver excellent results. It will help enhance user experience as well. Let us take a look at the tragic example of the 737 Max. Here, the software was designed to automatically lower the plane’s nose if it senses that the nose was rising too high. When this system malfunctioned, the pilots only had a few seconds to react. They were not even aware that this was a part of the plane’s design. This example underscores the need for AI to work in harmony with humans. If the 737 Max had been designed to help humans make better decisions and not completely replace them, this tragic incident would not have happened.
“Technology should not aim to replace humans, rather amplify human capabilities”
Douglas Engelbart
Keep Humans in Loop, Build Effective Models
Human-centered AI goes hand in hand with the human-in-loop approach. This means humans are involved in every step of the process, from training the model to testing and fine-tuning it. For instance, the training data used to teach a model can be labeled by humans. It can be used to teach the models what to look for, ensuring that it recognizes the right features. Whenever a model makes a mistake, humans can step in to correct it and provide valuable feedback. When we keep humans in the loop, we can create AI systems that complement us instead of replacing us, and we can trust that these systems will make the right decisions.
Know the Expectations, Understand the Relevance
When creating AI solutions, we should not focus on the technical aspects alone. We should take into account the humans who will be using them and the impact they will have on society. We need to ask the right questions: Who is this solution for? Why do they need it now? What do they expect from it? What is the importance of it now? Let us take the example of specialty pharmacy. Here, AI can alleviate the burden of managing administration tasks while pharmacists can focus on the patients more and provide them with better care. Thus, AI solutions can truly transform our society if people are at the center of the development process.
Also Read: Data Annotation and Artificial Intelligence’s Role in Agriculture
Spot the Bias, Mitigate Them
It is essential to be aware of the potential biases that can creep into the algorithms we rely on. Ensure that you are relying too heavily on either machine judgment or human judgment, as it can have serious consequences. It is always crucial to identify and mitigate any potential biases in your AI development process. Even the most advanced algorithms can be affected by human biases. Maintaining fair and unbiased results, therefore, requires regular monitoring and adjustment.
Understand the Environment, Anticipate the Impact
To build an inclusive AI, we must consider the social context in which it will operate. Here are the 2 approaches you need to consider:
- Assess the current state of the environment. For example, are people suffering from rare conditions treated the same way as those suffering from common conditions? Do patients who visit large medical centers get the same level of service compared to people who visit small clinics in rural areas? Are there any underlying human biases involved in any of the current operations?
- Take steps to anticipate the impact of artificial intelligence. For example, does the data include any underrepresented populations? What are the checks you need to implement to ensure that these underrepresented populations get quality care as well?
Collaborate with Multiple Domains, Analyze the Behaviour
To develop a successful human-centered AI, you need to collaborate with practitioners and scholars from diverse disciplines. It should include engineers, sociologists, anthropologists, designers, psychologists, and various other experts from multiple domains. You need to analyze human behaviors in different social contexts and apply domain knowledge to specific applications.
Create Low-Cost Prototypes, Incorporate Human-in-loop Design
Always start with low-cost prototypes that incorporate human-in-loop designs. This will help to validate the design and prevent any costly reworks at a later stage. By including potential errors an AI model might make, the prototype can be refined to improve accuracy. For example, design teams can use analog prototypes to test and refine their solution for extracting prescription and patient information from faxed documents.
The Final Say
Human-centered AI is not a mere destination you need to reach. It is an ongoing journey of continuous improvement and learning from our mistakes. By prioritizing responsible AI principles and keeping humans at the center of the design process, developers can create systems that deliver maximum results at minimum costs. Let’s strive to build AI that works for the people, not against them, and continue to evolve in this rapidly growing world.
Opporture has the expertise and resources to help you navigate this complex landscape. Contact us today to learn more about our AI model training services and how we can help you put humans first when it comes to responsible AI.
