Talks
Speakers
Events
Topics
Sign in
Home
Talks
Speakers
Events
Topics
Leaderboard
Use
Analytics
Sign in
Suggest modification to this talk
Title
Description
Keynote: Consequences of an Insightful Algorithm by Carina C. Zona Coders have ethical responsibilities. We can extract remarkably precise intuitions about people. Do we have a right to know what they didn't consent to share, even when they shared data leading us there? Balancing human needs and business specs can be tough. How do we mitigate against unintended outcomes? In this talk, we look at examples of uncritical programming, & painful results of using insightful data in ways that were benignly intended. You'll learn practices for examining how code might harm individuals. We’ll look at how to flip the paradigm, for consequences that are better for all.
Date
Summarized using AI?
If this talk's summary was generated by AI, please check this box. A "Summarized using AI" badge will be displayed in the summary tab to indicate that the summary was generated using AI.
Show "Summarized using AI" badge on summary page
Summary
Markdown supported
The keynote presentation "Consequences of an Insightful Algorithm" by Carina C. Zona at RubyConf 2015 emphasizes the ethical responsibilities of coders in the context of algorithm development and data use. Zona discusses the implications of utilizing algorithms to extract precise insights about individuals, raising crucial questions about consent and the potential unintended outcomes of such data-driven practices. Key points discussed include: - **Definition of Algorithms**: Zona describes algorithms as step-by-step processes designed to predict outcomes, applicable in both computer science and everyday scenarios. - **Consequences of Algorithms**: The talk highlights that algorithms can lead to consequences, often without the direct explanation or consent from affected individuals. - **Ethical Considerations**: Zona argues for the necessity of balancing human needs with business specifications, as uncritical programming can lead to painful real-world effects. - **Case Studies**: Zona provides several notable examples: - **Target's Pregnancy Ads**: A father's outrage over targeted ads illustrates the moral implications of data misuse when a retailer inferred personal information without explicit consent. - **Shutterfly's Congratulatory Emails**: Highlighting the discomfort caused by automated messages sent to customers, some of whom were dealing with infertility or loss. - **Facebook's Year in Review**: Discusses Eric Meyer’s experience with algorithmic insensitivity when the platform reminded him of painful memories related to his deceased daughter. - **Bias in Algorithms**: Zona covers various instances where algorithms have perpetuated bias, such as racial profiling in Google Ads and abusive uses of data by companies like Uber. - **Call to Action**: Zona urges coders to remain humble, recognize failure modes within their algorithms, and audit outcomes for biases. She emphasizes the need for transparency and accountability in algorithmic processes to create fairer, more ethical technology. - **Conclusion**: The ultimate takeaway from Zona's talk is a call for coders to advocate for users' best interests, ensuring that their work consciously considers the implications on individuals while aiming to avoid past mistakes.
Suggest modifications
Cancel
