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What are the best methods for measuring the social impact of algorithms?

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Algorithms are powerful tools that can automate tasks, optimize decisions, and generate insights. But they can also have significant social impacts, such as affecting people's privacy, rights, opportunities, and well-being. How can software designers measure and evaluate the social impact of their algorithms? In this article, we will explore some of the best methods and frameworks for assessing the ethical and social implications of algorithmic systems.

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Okan Yilmaz, PhD

Engineering Leader | Educator | Lifetime Learner
Can Delil Bozkurt
Dr. Rizwan Ahmed, PhD

Technology Leader ★ Entrepreneur ★ Keynote Speaker ★ Tech Evangelist ★ Startup Advisor & Angel Investor ★ Agile Coach…

1 Define the context

The first step in measuring the social impact of algorithms is to define the context in which they operate. This means identifying the goals, values, stakeholders, and risks involved in the problem domain and the algorithmic solution. For example, if you are designing an algorithm for hiring, you need to consider the objectives of the employer, the expectations of the applicants, the legal and ethical standards of the industry, and the potential biases and errors of the algorithm. By defining the context, you can establish the criteria and indicators for measuring the social impact of your algorithm.

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Can Delil Bozkurt
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Often times the algorithm itself is made unbiased but the data it’s trained on is biased. This doesn’t have to be the case, but if it is, then the algorithm will not accurately operate. Just keep this in mind when you are planning an algorithm.

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2 Apply a framework

The second step is to apply a framework that can guide you through the process of measuring the social impact of algorithms. A framework is a set of principles, methods, and tools that can help you analyze, evaluate, and improve your algorithmic system. There are many frameworks available for different purposes and domains, such as the Algorithmic Impact Assessment (AIA), the Ethical OS Toolkit, the Data Ethics Canvas, and the Fairness, Accountability, and Transparency (FAT) principles. By applying a framework, you can structure your approach and ensure that you cover the relevant aspects and dimensions of the social impact of your algorithm.

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3 Collect and analyze data

The third step is to collect and analyze data that can inform your measurement of the social impact of algorithms. Data can be quantitative or qualitative, and it can come from various sources, such as user feedback, surveys, interviews, observations, experiments, audits, and reports. The data should reflect the actual or potential effects of your algorithm on the stakeholders and the society at large. For example, if you are measuring the social impact of an algorithm for credit scoring, you need to collect data on how the algorithm affects the access, affordability, and fairness of credit for different groups of people. By collecting and analyzing data, you can measure the performance, outcomes, and impacts of your algorithm.

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Can Delil Bozkurt
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There are effectively 6 phases of data analysis: Phase 1: Data Discovery and Formation. Phase 2: Data Preparation and Processing. Phase 3: Design a Model. Phase 4: Model Building. Phase 5: Result Communication and Publication. Phase 6: Measuring Effectiveness.

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4 Interpret and communicate results

The fourth step is to interpret and communicate the results of your measurement of the social impact of algorithms. This means translating the data into meaningful insights, recommendations, and actions that can help you improve your algorithmic system and its social impact. For example, if you find that your algorithm has a negative impact on the privacy of your users, you need to explain why this happens, what are the consequences, and how you can mitigate or prevent it. By interpreting and communicating the results, you can share your findings and learnings with your stakeholders and the public, and foster trust and accountability.

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5 Monitor and update

The fifth step is to monitor and update your measurement of the social impact of algorithms. This means tracking the changes and trends in the context, data, and results of your algorithmic system over time, and adjusting your measurement accordingly. For example, if you discover that your algorithm has a new or unexpected impact on the environment, you need to update your criteria and indicators, collect new data, and reevaluate your results. By monitoring and updating your measurement, you can ensure that your algorithmic system remains relevant, responsive, and responsible.

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Okan Yilmaz, PhD

Engineering Leader | Educator | Lifetime Learner
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In its C2B "Smart Business" model, Ali Baba has used experimentation to determine what customers want and enhanced their solution accordingly. They have optimized their network coordination and data intelligence algorithms based on the customer behavior. In the business models driven by customer feedback, monitoring the results and updating the model based on customer activity is the key for success. In most cases, these solutions are built for customers that don't exist or for existing customers with behaviors which evolve during the interaction with these solutions. For example, ByteDance did not become a multibillion dollar company by inventing video streaming. They created and enhanced TikTok iteratively based on customer behaviors.

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Dr. Rizwan Ahmed, PhD

Technology Leader ★ Entrepreneur ★ Keynote Speaker ★ Tech Evangelist ★ Startup Advisor & Angel Investor ★ Agile Coach ★ Author
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In order to measure and evaluate the social impact of algorithms, we need to look at factors like potential biases and errors in the algorithm impacting some people. We can use the frameworks available to collect and measure the social impact of the algorithm. Accordingly we need to revise our algorithm which should work more responsibly without social impact.

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6 Engage and collaborate

The sixth and final step is to engage and collaborate with others in measuring the social impact of algorithms. This means involving and consulting with the stakeholders and the experts who have an interest or a knowledge in the problem domain and the algorithmic solution. For example, if you are measuring the social impact of an algorithm for health care, you need to engage and collaborate with the patients, the doctors, the regulators, and the researchers who can provide valuable insights, perspectives, and feedback. By engaging and collaborating with others, you can enrich your measurement and improve your algorithmic system and its social impact.

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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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What are the best methods for measuring the social impact of algorithms?

1

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3

4

5

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1 Define the context

2 Apply a framework

3 Collect and analyze data

4 Interpret and communicate results

5 Monitor and update

6 Engage and collaborate

7 Here’s what else to consider

Software Design

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What are the best methods for measuring the social impact of algorithms?

1

2

3

4

5

6

7

1 Define the context

2 Apply a framework

3 Collect and analyze data

4 Interpret and communicate results

5 Monitor and update

6 Engage and collaborate

7 Here’s what else to consider

Software Design

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