How would you design Uber for blind people?

Introduction

We're tasked with designing an Uber-like service specifically for blind users. This involves reimagining the ride-hailing experience to cater to the unique needs of visually impaired individuals. Our goal is to create a safe, accessible, and empowering transportation solution that enhances mobility and independence for blind users.

Clarify Questions (3 minutes)

• Is this a standalone product or an extension of the existing Uber ride platform? Is Uber eats in the scope?

• Why it matters: This impacts our development approach and available resources.
• Hypothetical answer: It's an extension of the existing Uber platform. Uber eats is not in scope.
• Impact: We can leverage Uber's existing infrastructure and user base.

• Are there any specific regulatory requirements or accessibility standards we need to consider?

• Why it matters: Compliance is crucial for legal and ethical reasons.
• Hypothetical answer: Yes, we need to comply with ADA guidelines and WCAG 2.1 standards.
• Impact: This will guide our design decisions and feature prioritization.

• What's our target market? Are we focusing on a specific geographic region or going global?

• Why it matters: This affects localization efforts and market strategy.
• Hypothetical answer: We're starting with major U.S. cities before expanding globally.
• Impact: We'll need to consider regional differences in infrastructure and support services.

Propose the Goal

I believe that the primary reason for Uber to undertake this initiative now is due to these factors:

1. Aging population: As the population ages, the number of visually impaired individuals is likely to increase, expanding our potential user base.
2. Growing focus on accessibility: There's increasing expectation on companies to make their products and services accessible to all users.
3. Advancements in assistive technologies: Innovations in voice recognition, haptic feedback, and AI can be leveraged to create a better user experience.

I believe our goal is to create a seamless, safe, and empowering ride-hailing experience for blind users that matches or exceeds the convenience of the standard Uber service. Does this align with your vision?

Define the Scope

For this product design challenge, let's focus on the core ride-hailing experience for blind users, including booking, waiting for, and taking a ride. We'll assume we're building on top of Uber's existing platform and starting with major U.S. cities. Before designing the experience, I will touch base on competitive offerings.

Competitor Analysis

Currently, there are few dedicated ride-hailing services for the blind. Some existing solutions include:

1. Aira: Provides visual interpretation services but isn't specifically for transportation.
2. Be My Eyes: Offers volunteer-based visual assistance but isn't focused on ride-hailing.

Uber itself has some accessibility features, but they're not comprehensive for blind users. Our strengths lie in our existing infrastructure and driver network. Our weakness is the current app's reliance on visual interfaces.

Case Study: Waymo's self-driving cars have been testing features for blind passengers, including Braille labels and audio cues. This demonstrates the potential for technology to enhance mobility for visually impaired individuals.

Value Chain Analysis

In the transportation industry for individuals with visual impairments, several challenges remain unresolved: Pre-ride experience: Ensuring accurate ride booking. During the ride: Addressing safety concerns and accommodating specific needs. Post-ride experience: Verifying that the user had a positive experience.

User Segments (5 minutes)

Key stakeholders in this ecosystem include:

1. Blind users
2. Partially sighted users
3. Drivers
4. Caregivers or companions

We'll focus on blind users as our primary segment, as specified in the question.

Sub-segments of Blind Users

1. Tech-savvy young adults (18-35)
2. Working professionals (36-55)
3. Seniors (56+)
4. Students (high school and college)

Prioritization Table

The Total Score in the table is calculated as the product of the scores for TAM (Total Addressable Market), Engagement Potential, and Monetization: TAM (Total Addressable Market): The total number of potential users in the target segment. Engagement Potential: The likelihood of users actively using the service regularly. Monetization: The potential revenue that can be generated from the segment.

Explanation:

• Working professionals score highest due to their larger TAM, high engagement potential (regular commutes), and strong monetization prospects (steady income).
• Tech-savvy young adults come second, with high engagement potential but slightly lower TAM and monetization.
• Seniors have a decent TAM but lower engagement and monetization potential.
• Students have the smallest TAM and lowest monetization potential, despite good engagement.

Based on this analysis, we'll focus on working professionals as our primary user segment.

Pain Points (5 minutes)

For working professionals who are blind, key pain points include:

1. Difficulty in requesting the Uber. To request an Uber an unassisted visually impaired user faces challenges in communicating precise pickup and drop location and then confirming the price to book an Uber.

• User quote: "It's frustrating when drivers can't find me or don't know exactly where to drop me off."
• Metric: Average time spent on location confirmation during booking

2. Difficulty identifying the correct vehicle

   • User quote: "I'm always anxious about getting into the wrong car."
   • Metric: Number of reported incidents of users entering incorrect vehicles

3. Lack of real-time, non-visual updates on ride status and ETA

   • User quote: "I never know exactly when my ride will arrive or where it is."
   • Metric: User-reported satisfaction with ride status updates

4. Concerns about driver awareness and preparedness for assisting blind passengers

   • User quote: "Some drivers don't know how to interact with or assist a blind passenger."
   • Metric: Number of complaints related to driver assistance

Prioritization of Pain Points (3 minutes)

The table evaluates pain points based on their Severity, Frequency, and a combined Total Score to prioritize issues with the greatest impact on user experience. Severity: The intensity of the impact this pain point has on the user experience. Frequency: How often users encounter this pain point during their journey.

Based on this analysis, we'll focus on addressing the top two pain points: vehicle identification and booking a cab.

Reasoning: Vehicle identification scores highest due to its critical impact on safety and user confidence. Booking a cab is equally important as this sub-segment of users often use cabs to commute to their workplace on a daily basis , While non-visual updates and driver preparedness are important, they have a slightly lower impact on the core functionality and safety of the service.

Solution (10 minutes)

Creative Solutions

1. "AI Concierge" - An AI-powered voice assistant that guides users through the entire ride process. The concierge assists with the user to book a ride and also be updated about ride status before and during the ride.

2. "Sound Beacon" - A unique audio signal emitted by the driver's phone to help users locate the vehicle when they are in close vicinity.

3. "Tactile Map" - A Braille-enabled smartphone case that provides haptic feedback for navigation.

4. "Driver-Passenger Bridge" - A two-way audio communication system activated upon ride confirmation.

5. "Specialized Training" - Fleet of drivers equipped and trained to provide additional support visually impaired passengers

6. Moonshot: "Neural Navigation" - A brain-computer interface that transmits spatial information directly to the user's mind.

Prioritization Table

The Total Score in this modified version of RICE Framework is calculated by summing up the individual scores for each factor: Total Score=Reach+Impact+Effort (inverted)+Alignment Here’s a breakdown of each factor: Reach: How many users are likely to benefit from this solution. Impact: How significantly the solution will improve the user experience or solve the problem. Effort (inverted): Lower effort gets a higher score. This is to prioritize solutions that are easier to implement relative to their benefits. For example: If a solution has an Effort = 7, it means it is moderately challenging to implement. The score reflects how feasible it is to prioritize. Alignment: How closely the solution aligns with organizational goals and values (e.g., improving accessibility).

Explanation:

• Sound Beacon: High reach and alignment, moderate effort
• AI Concierge: High impact and alignment, moderate effort
• Driver-Passenger Bridge: Good balance of all factors
• Tactile Map: Lower reach due to hardware requirements
• Specialized Training: High impact and reach, with moderate effort for implementation
• Neural Navigation: Highest impact but lowest feasibility

Based on this analysis, we'll focus on the AI Concierge solution.

User Flow for AI Concierge

1. User opens the app and is greeted by the AI assistant
2. AI guides user through ride booking process using voice commands
3. AI provides real-time updates on driver location and ETA
4. Upon driver arrival, AI assists in vehicle identification
5. During the ride, AI offers navigation updates and estimated time to destination
6. At drop-off, AI confirms safe arrival and ends the ride

Potential Challenges

1. Ensuring accurate natural language processing in noisy environments - Users may interact with the AI in crowded, noisy, or outdoor settings where ambient sounds could interfere with the system's ability to interpret commands. Robust noise-canceling technology and contextual understanding are needed to ensure reliability.
2. Balancing verbose guidance with user efficiency and preference - Providing detailed instructions is essential for clarity, but excessive verbosity might frustrate users or slow down the process. Striking a balance by allowing users to customize the level of detail is crucial for maintaining both usability and satisfaction.
3. Integrating the AI system with Uber's existing infrastructure - Seamlessly connecting the AI concierge with Uber’s systems (e.g., booking, driver communication, and payment) requires addressing compatibility issues, ensuring data security, and minimizing potential disruptions to existing operations.

Success Metrics (5 minutes)

User Metrics:

1. User satisfaction score for blind passengers: This measures the overall satisfaction of blind passengers with the service.
2. Reduction in time spent identifying correct vehicles: This measures the decrease in time blind users spend locating their assigned vehicle.
3. Decrease in reported safety incidents: This measures the reduction in safety incidents reported by visually impaired users.

Product Metrics:

1. Adoption rate among blind users: This measures the percentage of blind users adopting the accessible features of the service.
2. Ride completion rate for trips booked through the accessible interface: This measures the percentage of completed rides initiated via the accessible booking interface
3. Average time from ride request to vehicle identification: This measures the average time it takes for visually impaired users to identify their vehicle after requesting a ride.

Leading Indicators:

1. Number of ride requests made using voice commands: This measures the number of rides initiated by blind users through voice command features.
2. Positive feedback on AI assistant interactions: This measures the volume of positive user feedback related to AI assistant interactions.
3. Reduction in customer support tickets related to accessibility issues: This measures the decrease in customer support tickets concerning accessibility problems.

These metrics align with our goal of creating a seamless, safe experience for blind users and address the key pain points of vehicle identification and communication.

Summary

We've designed an AI Concierge system for Uber that caters specifically to blind users, focusing on working professionals. This solution addresses the critical pain points of vehicle identification and location communication through an intelligent voice-guided interface. By leveraging advanced AI and voice recognition technology, we can create a more inclusive and accessible ride-hailing experience.

Our approach aligns with Uber's commitment to accessibility and leverages the company's existing infrastructure. Key success metrics include user satisfaction, safety improvements, and adoption rates among blind users.

Next steps would include prototyping the AI Concierge, conducting user testing with blind individuals, and iterating based on feedback.

Expand Your Perspective

• How might this solution be adapted for users with other disabilities, such as hearing impairments?

• What are the potential implications of this technology for the broader field of accessible design?

• How could this system be scaled to work in countries with different languages and cultural norms around assistance for blind individuals?

Related Topics

• Ethical considerations in AI-assisted accessibility solutions

• Integration of haptic feedback technologies in mobile applications

• Balancing automation and human interaction in assistive technologies

• Privacy concerns in AI-powered accessibility features

• Universal design principles in transportation services",uber-design-for-blind-users,Uber Design for Blind Users | Product Design Interview