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What do you do if you suspect bias in evaluating performance for Web3 roles?

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In the evolving world of Web3, where decentralized technologies and blockchain underpin roles and responsibilities, it's crucial to ensure that performance evaluations are fair and free from bias. Web3, short for "web 3.0," represents the third generation of internet services for websites and applications focused on utilizing a machine-based understanding of data to provide a data-driven and Semantic Web. The decentralized nature of Web3 can sometimes obscure the transparency of performance evaluations, leading to concerns about bias. If you suspect bias in evaluating performance for Web3 roles, it's important to approach the situation methodically to ensure that all team members are assessed fairly.

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Altug Tatlisu

CEO @ Bytus Technologies | Web3, Decentralized Applications (DApps) | Smart Contracts | Blockchain Solutions |…
Rajat Bhardwaj

Head of Enterprise Support @ AWS in India for Startups , Retail , EduTech & Public Sector. Ex Broadcom Inc., Computer…
Yasaman T.

Technology Transformation and Security Advisor | Fractional CISO| Corporate Audit| Governance, Risk, & Compliance |…

1 Recognize Bias

If you suspect bias in performance evaluations within Web3 roles, your first step is to identify its forms. Bias can manifest as favoritism, prejudice, or even a lack of understanding of Web3's unique requirements. It's crucial to reflect on whether certain individuals are consistently rated higher or lower without clear justification or if there are patterns that suggest certain demographics are being disadvantaged. Recognizing bias requires a critical look at both qualitative and quantitative aspects of performance reviews.

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Altug Tatlisu

CEO @ Bytus Technologies | Web3, Decentralized Applications (DApps) | Smart Contracts | Blockchain Solutions | Cryptocurrency Payment Gateways
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If you suspect bias in evaluating performance for Web3 roles, it is important to gather evidence of the bias and discuss your concerns with HR or a trusted supervisor. Transparency and objectivity in performance evaluations are essential for a fair assessment.

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Rajat Bhardwaj

Head of Enterprise Support @ AWS in India for Startups , Retail , EduTech & Public Sector. Ex Broadcom Inc., Computer Associates, Nokia Networks, Agilent Technologies, Idea Cellular and startups
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Always consciously retrospect the possible biases while evaluating performance of individuals or a team. Top three biases influencing decision making for web3 roles are : 1. Halo effect It occurs when we perceive one great thing about a person or team for a single UI or feature. Let that halo glow of that one thing color our opinions of everything else. 2. Horns effect It occurs when perception of someone is unduly influenced by one negative trait. Judge performance holistically. 3. Conformity Bias Let the data speak. Don't get influenced by overall results which can be unfavourable, despite the individual putting in 200%. UI and UX engineers are the digital face for an organisation. Recognise and reward the ones who #raisethebar.

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Yasaman T.

Technology Transformation and Security Advisor | Fractional CISO| Corporate Audit| Governance, Risk, & Compliance | Harvard Certified
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One thing I’ve found helpful is documenting the definition of bias in each role and define the borderlines transparently, then collecting the examples, feedback and compare to other individuals with the similar roles and responsibilities. Also validating criteria used for evaluation is crucial, they need to be clearly defined with the objective specifically for each Web3 role.

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2 Gather Evidence

Once you've identified potential biases, it's important to gather evidence. Document instances where the evaluation criteria seem to be applied inconsistently. In the realm of Web3, this could involve reviewing code commits, project contributions, or community engagement in decentralized projects. Ensure that your evidence is concrete and relates directly to job performance, without being influenced by personal feelings or unrelated factors.

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3 Open Dialogue

After collecting evidence, initiate a constructive dialogue with the relevant parties. This could be with a supervisor, human resources, or a Web3 project lead. Approach the conversation with a focus on seeking clarity and improvement rather than assigning blame. Present your findings calmly and suggest that a more structured, transparent evaluation process could benefit the team and the project's success in the decentralized ecosystem.

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Yasaman T.

Technology Transformation and Security Advisor | Fractional CISO| Corporate Audit| Governance, Risk, & Compliance | Harvard Certified
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For this to happen, it needs to be a safe space for team members to be created that they can discuss their concerns without any fear of retaliation!!! Hardly can find such a work place!!!.

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4 Propose Solutions

Proposing solutions is key to addressing bias in performance evaluations. One approach is to suggest implementing more objective metrics tailored to Web3 roles, such as smart contract deployment success or community feedback on decentralized applications (dApps). Encourage the adoption of tools that facilitate unbiased peer reviews and foster a culture of continuous feedback, which is particularly valuable in the rapidly changing Web3 space.

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5 Educate Peers

Education is a powerful tool in combating bias. Share knowledge about the importance of fair performance evaluations with your peers. Discuss how bias can hinder the innovative potential of Web3 by demotivating talented contributors or by not recognizing their valuable input. Promote an inclusive culture where diverse perspectives are valued and where performance is judged on merit and contribution to the decentralized community.

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6 Reflect and Adjust

Finally, it's essential to reflect on the outcomes of your actions and be prepared to adjust your approach if necessary. The dynamic nature of Web3 means that performance evaluation processes may need to evolve as the technology and roles within it develop. Continuously seek feedback on the effectiveness of any new measures put in place and remain vigilant for signs of bias, adjusting strategies as needed to ensure fair and equitable evaluations.

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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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Yasaman T.

Technology Transformation and Security Advisor | Fractional CISO| Corporate Audit| Governance, Risk, & Compliance | Harvard Certified
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I think having an external 3rd party audit can be considered to evaluate process for biases, they can assess and provide improvement plans.

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What do you do if you suspect bias in evaluating performance for Web3 roles?

1

2

3

4

5

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7

1 Recognize Bias

2 Gather Evidence

3 Open Dialogue

4 Propose Solutions

5 Educate Peers

6 Reflect and Adjust

7 Here’s what else to consider

Web3

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What do you do if you suspect bias in evaluating performance for Web3 roles?

1

2

3

4

5

6

7

1 Recognize Bias

2 Gather Evidence

3 Open Dialogue

4 Propose Solutions

5 Educate Peers

6 Reflect and Adjust

7 Here’s what else to consider

Web3

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