How do you create a great human-robot experience?

The key here is to understand that we are talking about augmentation and collaboration. Users must be comfortable to work alongside a robot, or any AI app, as they would working alongside a human, and must do so by impartially evaluating the robot's skills and performance.

Understand your users! When designing a robot, it's essential to keep the end-user in mind. The robot should serve a purpose and provide value to the person who interacts with it. To create a great human-robot experience, you need to understand the needs, preferences, and limitations of the people who will use it. Another critical factor in creating a great human-robot experience is to design the robot's interface with the user in mind. You need to consider the user's emotional response. A robot that is too robotic or that behaves in unexpected ways can be disconcerting or even frightening to users. On the other hand, a robot that is too human-like can create unrealistic expectations and lead to disappointment.

When we talk about human-robot interaction, an inherent concept is that they are not acting in silos, but there is a human and robot , as well as possibly robot robot interaction involved. To make this interaction a great experience, it is vital to understand the users and create personas. This understanding can be built using research methods such as interviews, observations, surveys. There is another way researchers try understanding users is mimicing a real life situation such as of a home and observing / recording robot behaviour as a home assistant with the residents. This helps to understand when the robot acted intelligently and when the robot made stupid mistakes. This helps to understand the expectations of a user in such a setup.

Creating a great human-robot experience involves a combination of technology, design, and human-centric principles. Conduct user research to understand the specific needs and goals of your target audience. Create user personas to represent different user types and their preferences.

Talk to people to learn what they need and want from the robot. Watch people use it and then important to get their feedback. The key resides in balancing functionality, humanlikeness and approachability.

The uncanny valley hypothesis states that users might experience eerie when interacting with almost but not fully human-like artificial characters. Usually when a robot looks or almost resembles a human being, people start believing that the robot is human and expects the robot to act and feel like human. This sets false expectations from a robot. For instance, an iRobot which doesn’t look like a human but does what it is designed to really well. Alexa is a robot that is designed to be a vocal intelligent bot. So, it’s essential that a robot does what it is intended to do and it’s appearance also matters to set the expectations right!!

The key to success is one word: Authenticity. When something is truly and completely offending we can learn to trans and bond with it. If that trust and authenticity is not there then we become uneasy. That's why today's digital humans despite their near photo realistic appearance, still appeak creepy in their mannerisms and 'dead eyes' appearance. It's called Uncanney Valley and its extremely hard to get past. On the other hand, Pixar characters don't look perfectly human but we can easily bond with them. I would make 3D avatars clearly synthetic in a cartoon robot way, so people know what the are dealing with.

Design goes beyond just aesthetics; it's about the robot's overall 'persona.' Have we ever thought about what 'charm' a robot might have? Take WALL-E for example, a fictional robot but one with a ‘personality’ that most people fell in love with. Imagine creating a robot with its own set of 'soft skills'—now that would take human-robot interaction to a new level!

The appearance and behavior of your robot should serve a clear purpose. Its aesthetics, movements, and communication methods should resonate with the user's context. If it's a healthcare robot, a friendly and approachable appearance might be ideal, while an industrial robot should prioritize functionality over aesthetics.

It is critical that a robot performs the tasks it is intended to do without risking or disrupting human lives. For example, initially when Alexa was launched, there were concerns people had that it is listening even when we don’t want it to. Slowly people got acquainted with how Alexa works and captures information and it doesn’t violate your privacy concerns. On similar lines, automated vehicles were launched and first concern people raised was how would an autonomous vehicle would behave around pedestrians and other autonomous vehicles. But with time, knowledge about the vehicles was unveiled and people understood how it takes care of safety of passengers and pedestrians.

Once the problem is understood for which the AI solution would help with decision making understand the ethical standards and principles, including transparency, fairness, and data privacy. Ensure that your AI solution respects users' rights and values. Design UX interfaces and interactions that are easy to use and accessible to all, including individuals with disabilities. Follow accessibility guidelines and best practices. Provide clear and understandable information about the AI system's capabilities, limitations, and how it makes decisions. Incorporate feedback mechanisms to collect user input and improve the AI system continuously. Listen to user concerns and adapt the solution accordingly.

Couldn't agree more about adhering to human-robot interaction principles. It reminds me of Asimov's laws of robotics, which although fictional, set an early framework for this discussion. I believe the principle of 'empathy' could add another layer. The robot doesn’t need to 'feel,' but simulating empathy could facilitate a more natural interaction and also increase user trust.

Respect user autonomy, maintain transparency, adapt to preferences, and ensure safety. Users should feel in control and trust their robot companions. Design interactions that are intuitive and user-friendly, with feedback mechanisms that keep users informed about the robot's intentions and actions.

If a robot is really good but it’s not able to gain trust of the targeted audience due to some reasons, then those people do not wish to use the robot in their daily lives. Thus it is vital that the robot is tested , observed in real-time settings where it interacts with humans. The settings should be such that there is no interference from observants. And, a thorough experimentation can be done with diverse scenarios. For example, a daycare assistant robot should be tested on how it works with agitated kids, how it handles a sick kid situation, how it behaves when there is an intruder or a threat, how it acts with an infant when infant is fussy and not able to tell about the problem.

Make the AI's decision-making process transparent to users. Provide explanations for recommendations or actions taken by the AI. Consider diverse user demographics and ensure that your AI solution caters to a wide range of cultural, linguistic, and demographic backgrounds.Provide users with a sense of control over the AI system. Allow them to customize settings, opt-out, or modify AI recommendations as needed.

In order to evaluate your himan- robot interaction, you will need to test it. And I mean rigorous testing. Testing the interaction in different situations and environments and with diverse users will shed dome lights on any shortcomings or limitations.

Metrics are the compass guiding any innovation. However, what scales should we use to measure 'trust' or 'empathy'? These qualitative aspects are tricky but vital. In the end, a robot is not just a tool but an 'entity' that participates in the social fabric, and the evaluation metrics should reflect that.

Conduct observational studies where researchers or experts closely observe users interacting with the robot. This can reveal non-verbal cues and behaviors that may not be captured through surveys alone. Ethical and Social Impact Assessment can be another way to evaluate your human robot experiences based on trustworthiness, user acceptance, and the robot's level of responsibility in various scenarios.

Iteration is where the real magic happens. And let's not forget, failure here isn't a setback; it's more data. If a certain interaction model didn't work as expected, that’s a rich resource to understand 'why.' Every flaw is a brushstroke in the bigger picture of perfecting the human-robot experience.

Customize the robot's behavior and responses to individual user preferences when applicable. Utilize machine learning and AI to adapt to user behavior over time.

se the insights gained from evaluation to refine your robot's design. Embrace innovation and stay updated with the latest HRI research. The field is dynamic, and new technologies can enhance your robot's capabilities.

The idea of learning from others is crucial. Many industries are just beginning to see the value of Human-Robot Interaction. Whether it's healthcare, logistics, or even creative arts, each domain offers unique lessons that can enrich the broader field. A robot assisting a surgeon could teach us something valuable about precision, while a robot in a warehouse might highlight efficiency.

Don't reinvent the wheel. Study existing examples of successful human-robot interactions and engage with the HRI community. Learning from others' experiences can expedite your own journey to creating a remarkable human-robot experience. Remember, a great human-robot experience doesn't merely fulfill a function; it also fosters a positive emotional connection between users and machines. Strive for a seamless blend of functionality and empathy in your robot's design to ensure it not only assists but also enriches the lives of those it interacts with.

To create a great human-robot experience, one needs to focus on: 1. user needs and pain points. 2. user-friendly interface. 3. user's emotional response (friendly, trustworthy). Example of steps involved: - Conduct user research. - Create user personas and user flows. - Prioritize simplicity and clear language in interface design. - Foster user confidence and control. - Implement NLP and ML for natural interactions and personalization. - Make the robot adaptable and align its personality with the brand. Follow these principles and tips for a delightful user experience.

We will lose a great deal when human teachers are replaced by infallible & 'unbiased' robots/personalities utilizing AI. When children feel more comfortable being guided by a comprehensive machine & neural network. One such AI-based education product is the Moxie Robot. Developed by Embodied, Inc., Moxie is designed to help children improve their social, emotional, and cognitive skills. The robot engages children in conversation, asks questions, and provides feedback and encouragement, all while tracking their progress over time. It is the first thing children want to see upon awakening; & it is what they want to lull them to sleep at night. It has replaced many roles previously performed by both parents & grandparents/ a slippery slope.

Creating a great human-robot experience involves understanding users, purposeful design, adherence to interaction principles, rigorous evaluation, iterative improvements, and learning from others. Consider cultural sensitivity, long-term relationships, privacy, accessibility, ethics, emotional intelligence, user education, ecosystem integration, aesthetics, and sustainability to enhance the experience.

Consider to create a collaboration of Humans & Robots which leverages the best of both skillsets. Build automated workflows and optimal processes enabled by technology but enlightened by Humans where there is value.