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Case study group discussion

Instruction and application
In Progress

Case study: Ethical dilemmas in AI-powered sentiment analysis​

In this activity, you will analyse an AI-driven sentiment analysis scenario, identify ethical risks and apply ethical frameworks to propose responsible AI solutions.

These skills help organisations navigate AI ethics challenges, ensuring transparency, fairness and compliance when using AI for customer insights, automated decision-making and data-driven strategies. Applying ethical principles in AI development can enhance trust, mitigate risks and align AI practices with regulatory standards in your workplace.

### Case study details

StyleSync, a global fashion retailer, leverages AI-driven analytics to track fashion trends and gain deeper insights into customer preferences. As part of its commitment to sustainability, the company recently launcheda new eco-friendly clothing line and aims to measure public reaction to the initiative. To refine its marketing strategies and sustainability messaging, StyleSync seeks real-time consumer insights. To achieve this, the company employsAI-powered sentiment analysis, analysing social media discussions to gauge customer sentiment and understand how its sustainability efforts are resonating with the market.

How data is collected and processed​

**Social media scraping:**StyleSync collects public social media posts, comments and hashtags related to its sustainability campaign to identify emerging trends.**Third-party data purchase:**To enhance its insights, StyleSync purchases aggregated sentiment data from third-party providers — without verifying how the data was sourced.**Sentiment analysis:**AI models categorise responses as positive, neutral or negative, allowing StyleSync to refine its marketing and engagement strategies.

Ethical dilemmas​

**Lack of user consent:**Customers are not informed that their social media posts are being collected and analysed for business insights.**Potential identification:**Even anonymised sentiment data can sometimes be traced back to individual users, raising privacy risks.**Bias in AI models:**The AI model may misinterpret sarcasm or regional dialects or overrepresent certain demographics, leading to skewed or unfair insights.

Activity instructions​

Work with your group to complete the following tasks:

Review the case study​

Review the StyleSync case study, and identify the ethical and privacy concerns related to AI-powered sentiment analysis. Consider the data collection methods, user consent issues and potential biases in the AI model.

Analyse AI ethics risks​

Analyse the ethical challenges in the case study. Use the following prompts to guide your discussion:

  • What are the main privacy risks in collecting and analysing social media data?
  • How does user consent factor into the company’s data collection strategy?
  • Could there be biases in the sentiment analysis model?
  • How might regulations like GDPR or CCPA apply to this scenario?

Apply an ethical framework​

Collaborate with your group to select one of the following ethical frameworks:

Regroup and share insight​

Return to the main session after 20 minutes to discuss key insights and recommendations.

Action item: Activity share out​

  • What is one major ethical insightyour group discovered in the case study?
  • What is one action step you would recommend to StyleSync to ensure responsible AI governance?