PART 4: TRANSLATING RESEARCH INTO POLICY

PART 4: TRANSLATING RESEARCH INTO POLICY

Much of what we know about ethical and policy issues in data science has been produced by in-depth empirical studies of real-world cases and applications. These studies are typically presented in lengthy articles aimed at academic audiences. However, policy- and decision-makers often lack the time necessary to read these papers. As a result, research into data ethics often has little impact on decision- and policy-making.

The aim of this assignment is for you to translate a research article (from the list below) presented in a scholarly journal into a one-page policy memo that can be readily digested by a key decision- or policy-maker. As well as providing a clear summary of the key issues involved in the case, you will also formulate three concrete recommendations to guide the policy- or decision-maker in addressing issues raised by the case.

Your memo should have a maximum length of one page (single-spaced).

A policy memo presents information about an issue and offers recommendations to decision-makers. A good policy memo will help the decision-maker to understand the issue and to make sound decisions about how to address the issue. Decision- makers want to be able to understand issues quickly and accurately. A policy memo should present information concisely and clearly.

For this part of the assignment, you have to translate an academic case study into a memo addressed to a key decision-maker. First, you will need to identify a single relevant decision-maker. The decision-maker wants to understand the main ethical issues raised by the case, and wants your guidance on how to address these issues.

Possible choices for a decision-maker include (but are not limited to):

Chief Information Officer of a technology company (e.g., social media company, mobile phone company) or other organization (e.g., a government agency, police force);

A government policy- or lawmaker (e.g., a politician or civil servant).

The memo should contain the following sections:

Header (1 mark). This header should contain your name, the recipient of your memo, and the title of your memo;

Introduction (3 marks). The Introduction should briefly describe the case you are addressing, and why the case is important and requires action on the part of the decision-maker;

Methods (3 marks). Briefly describe the methods that were used to conduct the case study.

Analysis of Issue (6 marks). Present an analysis of the main issues in. the case, drawing on the case study document;

Recommendations (12 marks). Devise and present three recommendations for addressing the issue.
For each recommendation:

explain briefly why the recommendation will help to address the issue;

how urgently the recommendation should be implemented;

how the recommendation can be implemented (e.g., what will the organization have to do to implement the recommendation?);

any difficulties that may be encountered with implementing the recommendation.

 

Style of your memo (5 points).  In terms of style, a good memo should be:

Professional in tone, including attention to grammar;

Logical and well-organized;

Persuasive;

Clear and concise. Sentences should be short and direct;

Jargon-free.

 

You should choose one of the following case studies:

Albury, K., Burgess, J., Light, B., Race, K., & Wilken, R. (2017). Data cultures of mobile dating and hook-up apps: Emerging issues for critical social science research. Big Data & Society, 4(2), 2053951717720950. https://doi.org/10.1177/2053951717720950

Joyce, D. (2017). Data associations and the protection of reputation online in Australia. Big Data & Society, 4(1), 2053951717709829. https://doi.org/10.1177/2053951717709829

Kubler, K. (2017). State of urgency: Surveillance, power, and algorithms in Frances state of emergency. Big Data & Society, 4(2), 2053951717736338. https://doi.org/10.1177/2053951717736338

Levy, K., Kilgour, L., & Berridge, C. (2018). Regulating Privacy in Public/Private Space: The Case of Nursing Home Monitoring Laws. Elder Law Journal, (2), 323364.

Papakyriakopoulos, O., Hegelich, S., Shahrezaye, M., & Serrano, J. C. M. (2018). Social media and microtargeting: Political data processing and the consequences for Germany. Big Data & Society, 5(2), 2053951718811844. https://doi.org/10.1177/2053951718811844

Selwyn, N., & Pangrazio, L. (2018). Doing data differently? Developing personal data tactics and strategies amongst young mobile media users. Big Data & Society, 5(1), 2053951718765021. https://doi.org/10.1177/2053951718765021

Taddeo, M. (2016). Data philanthropy and the design of the infraethics for information societies. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2083), 20160113. https://doi.org/10.1098/rsta.2016.0113

West, J. (2017). Data, democracy and school accountability: Controversy over school evaluation in the case of DeVasco High School. Big Data & Society, 4(1), 2053951717702408. https://doi.org/10.1177/2053951717702408