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Last updated on 2024年7月8日

How can you build trust when working with AI?

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Trust is essential for successful human-computer interaction, especially when it comes to artificial intelligence (AI). AI systems can perform complex tasks, provide insights, and automate processes, but they also pose challenges and risks that require careful consideration and communication. How can you build trust when working with AI, whether as a user, a developer, or a stakeholder? Here are some tips and best practices to help you foster a trusting relationship with AI.

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1 Understand the AI system

The first step to building trust is to understand how the AI system works, what it can and cannot do, and what its limitations and assumptions are. You need to have a clear idea of the system's goals, inputs, outputs, logic, and performance metrics. You also need to be aware of the potential biases, errors, and uncertainties that may affect the system's outcomes and decisions. By understanding the AI system, you can set realistic expectations, evaluate its reliability, and identify areas for improvement.

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Kim Killian

Director of Artificial Intelligence: Driving Innovation, Business Growth, and Competitive Advantage through ?AI-driven Solutions
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You build trust in AI by understanding how it works and uses data. Being transparent in how AI operates and open communication with Technology teams about AI capabilities and limitations helps. Regular interaction and feedback improve this initial understanding, leading to better user experiences and trust. When the users are engaged at the beginning of a project, they have more engagement and ownership, which builds trust not only in the AI but technology as a whole.

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Atharva Kodag

Electronics And Telecommunication engineering | Artificial Intelligence | Embedded Software Developer | Digital Signal Processing
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Understanding the AI System: Building Trust 1. Functionality: Understand how the AI system works and its capabilities. 2. Objectives and Outputs: Define its goals, inputs, and expected results. 3. Decision Making: Grasp the logic behind its decisions. 4. Performance: Evaluate how it measures success. 5. Biases and Uncertainties: Recognize potential biases and errors.

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2 Communicate with the AI system

The second step to building trust is to communicate with the AI system, both verbally and non-verbally. You need to establish a common language and a feedback mechanism that allows you to interact with the system effectively and efficiently. You also need to pay attention to the system's cues and signals, such as voice, tone, gestures, and emotions, that convey its state, intentions, and emotions. By communicating with the AI system, you can create a rapport, express your preferences and concerns, and resolve any conflicts or misunderstandings.

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Arlen Meyers, MD, MBA

President and CEO, Society of Physician Entrepreneurs, another lousy golfer, terrible cook, friction fixer
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Leadership is about earning the trust of followers. The AI medical industrial complex has to overcome several barriers to earn the trust of patients, doctors and healthcare executives. 1. The halo effect of previous bad behavior 2. In equitable access, cost and damage to the planet 3. Lack of clinical validation, generalizability and transparency 4. The barriers to end user implementation and dissemination 5. The tendency for doctors to make technology adoption errors

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3 Collaborate with the AI system

The third step to building trust is to collaborate with the AI system, both as a partner and a learner. You need to establish a shared vision and a mutual understanding of the roles and responsibilities of each party. You also need to leverage the strengths and complement the weaknesses of each party, and adjust your behavior and actions accordingly. By collaborating with the AI system, you can achieve your goals, learn from each other, and enhance your performance and satisfaction.

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Jaideep Kewalramani

LinkedIn Top Voice Artificial Intelligence | Entrepreneur | Growth Acceleration | Speaker | Startup | Angel | Non-Linear Transformation
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Creating a feedback loop between humans and AI will lead to better learning and productivity. Organisations and individuals must undertake structured pilots to measure the outcome of this feedback loop.

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4 Monitor and evaluate the AI system

The fourth step to building trust is to monitor and evaluate the AI system, both regularly and periodically. You need to track and measure the system's performance, outcomes, and impacts, and compare them with your expectations and standards. You also need to review and audit the system's processes, data, and algorithms, and check for any anomalies, deviations, or violations. By monitoring and evaluating the AI system, you can ensure its quality, accuracy, and compliance, and address any issues or risks.

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Justin McGee Odger

Hybrid DNA | WayFinder Capital | Deedable - Doing amazing things with data ??
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A great way to use monitoring and evaluation is ramping up the use of the model, and considering using stage-gates in the process. Consider using the following process: Idea > POC > MVP > Feature > Product At each stage of the process, monitor the results and evaluate if reaching a wider clientele is appropriate. Start small, monitor, evaluate, and grow.

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5 Ethical and transparent AI system

The fifth step to building trust is to ensure that the AI system is ethical and transparent, both in its design and its use. You need to follow the principles and guidelines of ethical AI, such as fairness, accountability, and explainability, and ensure that the system respects the values, rights, and interests of all stakeholders. You also need to disclose and document the system's information, methods, and decisions, and make them accessible and understandable to all stakeholders. By ensuring ethical and transparent AI, you can foster trustworthiness, responsibility, and legitimacy.

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6 Continuous improvement of AI system

The sixth step to building trust is to continuously improve the AI system, both in response to feedback and in anticipation of changes. You need to collect and analyze feedback from all stakeholders, such as users, developers, and regulators, and use it to improve the system's functionality, usability, and accessibility. You also need to monitor and anticipate the changes in the environment, such as new data, technologies, or regulations, and update the system accordingly. By continuously improving the AI system, you can maintain its relevance, adaptability, and innovation.

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Trish Staples

MBA | Healthcare Management
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Eventually, in healthcare, AI will learn and adapt to local populations and even specific physician feedback, but there are many regulatory and technical complexities to work through to get there.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Trish Staples

MBA | Healthcare Management
(已编辑)
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"No, you go first." Early adopters are the key to building trust in anything new. We need to support the Early Adopters, and then learn from them. All big changes start small.

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How can you build trust when working with AI?

1

2

3

4

5

6

7

1 Understand the AI system

2 Communicate with the AI system

3 Collaborate with the AI system

4 Monitor and evaluate the AI system

5 Ethical and transparent AI system

6 Continuous improvement of AI system

7 Here’s what else to consider

Artificial Intelligence

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How can you build trust when working with AI?

1

2

3

4

5

6

7

1 Understand the AI system

2 Communicate with the AI system

3 Collaborate with the AI system

4 Monitor and evaluate the AI system

5 Ethical and transparent AI system

6 Continuous improvement of AI system

7 Here’s what else to consider

Artificial Intelligence

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