Ethical Concerns in LLMs

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In recent years, advancements in artificial intelligence (AI) have led to the development of ChatGPT and other highly sophisticated generative language models and applications designed to generate human-like text and comprehend Natural Language. These generative AI models leverage deep learning techniques and vast amounts of data to recognize patterns, make inferences, and produce coherent and contextually relevant responses across a wide range of information. By mimicking human linguistic capabilities, these models have unlocked a multitude of applications, ranging from chatbots and virtual assistants to translation services and content generation tools.

While we have various advancements and conveniences, generative AI poses some ethical impacts as its response capabilities evolve. Specifically, software engineers must be aware of:

  • Privacy and data confidentiality risks (related to the AI ethics principle of Privacy)
  • Intellectual property (related to the AI ethics principle of Responsibility)
  • Collaboration at work (related to the AI ethics principle of Solidarity)
  • Workforce replacement (related to the AI ethics principle of Beneficence – social well-being and common good)
  • Bias (related to the AI ethics principle of Justice and fairness: involving issues like discrimination and injustice to minority, vulnerable, and underrepresented social groups).

During this week I visited the GPT laboratory in Pori and we discussed these concerns. Therefore, we have had a workshop on ChatGPT.

Fun fact: this blog post was assisted by an AI. Here’s to the wonders of technology!

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