Data Ethics & Policies

Data ethics is a foundational principle that guides the responsible, secure, and lawful management of data at Hamilton College. The college upholds rigorous internal policies and complies with external regulations to protect data integrity, ensure privacy, and promote ethical data use, all while encouraging a culture of accountability.

Hamilton Colleges’s data governance program is based on policies and procedures that provide guidance for classifying, accessing, utilizing, and retaining college data. The Director of Information Security determines if new or modified policies and procedures are needed and documents the college's data practices.

Hamilton College Policies:

Data Governance Policy

Data Classification Policy

Written Information Security Policy

Other

Click here to see all state and federal regularity agencies

Bias

There are many types of unconscious bias, and, unfortunately, not all of them are easy to detect. Understanding the different kinds that exist and how they may affect your judgment is the first step toward reducing their impact.

Let’s explore some common examples that can often influence our behavior and decisions without us even noticing:

• Affinity Bias: Our tendency to favor people who share similar interests, backgrounds, or experiences to our own.
• Gender Bias: The unconscious preference for one gender over another. This is most often seen in hiring practices and workplace interactions.
• Group Bias: The inclination to support or prefer members of our own group while being critical of those in other or new groups.
• Similarity Bias: Favoring individuals who we perceive as being like ourselves, which can limit diverse perspectives.
• Implicit Association: The automatic association we make between certain qualities and particular groups.
• Language Bias: Preferences based on someone’s native language or accent, which can affect communication and collaboration in diverse teams.
• Sexual Orientation Bias: The unconscious attitudes or stereotypes about people based on their sexual orientation, impacting inclusion and fairness.
• Confirmation Bias: The tendency to search for, interpret, and remember information that confirms our pre-existing beliefs.
• Halo Effect: The bias where our overall impression of a person influences how we feel and think about their character.
• Horns Effect: The tendency to allow one negative trait to overshadow all other traits of a person.

Unconscious bias exists but you do have control. Here are some resources to help you understand your biases. 

The Implicit Association Test (IAT) can be a useful tool in identifying potential biases, attitudes and associations, but these tests alone should not be expected to overcome the impact of biases of the test taker.

Kirwan Institute for the Study of Race & Ethnicity Implicit Bias Module Series.https://kirwaninstitute.osu.edu/implicit-bias-module-series

Implicit bias video series (University of California Los Angeles Equity, Diversity & Inclusion)https://equity.ucla.edu/know/implicit-bias/

7 short video clips discussing biases, schemas, attitudes, stereotypes, explicit and implicit bias.

Hamilton College LinkedIn Learning offers several courses on unconscious bias.

Becky, a data-phobics Journey in Data Literacy Comic Strip 

While Al is a valuable tool, please ensure responsible use:

• Do not upload sensitive, confidential, or personal data (e.g., FERPA-protected student information, HIPPA, etc.) into Al tools.
• Validate Al-generated outputs before using them in official reports or dashboards (critical thinking).
• Use Al for efficiency, and to help inform, decision-making-human oversight is essential.
• Respect intellectual property
• Limit access to certain types of data/documents
• Prompt hygiene rules to limit risky user prompts
• Retention of logs and prompts
• Follow all Hamilton College policies and guidelines when handling institutional data.

For more Information refer to the colleges Generative AI Guidelines

All Data Governance Resources