I was recently asked, “Forces that will shape the future in 2024 and beyond.”
Here is my answer:
Generative AI holds thrilling potential for LSPs. Ethical challenges abound, but we are optimistic that these can be addressed through human-AI collaboration.
AI is a technology tool, not a human, and has inherent flaws. And for all our flaws, we humans are emotionally intelligent, ethically discerning, and culturally aware – all attributes that are essential components of language access. Some of the challenges we contemplate daily include:
- Bias: Generative AI models are trained on vast amounts of data, and the quality and diversity of the training data plays a crucial role in their output. Human oversight can ensure that biases are not perpetuated or amplified.
- Privacy: LSPs handle large volumes of sensitive information. We must ensure that data protection and privacy standards are maintained rigorously.
- Accuracy: Human oversight and quality assurance processes should play a crucial role in ensuring that translations are accurate, culturally appropriate, and contextually relevant.
- Transparency: Being transparent about the use of Generative AI and its limitations is essential to maintain trust.
- Reskilling: Linguists are highly skilled individuals, prized for their judgement. LSPs should reskill and upskill their workforces, focusing on human-AI collaboration rather than complete automation.
Ideally, humans and technology will join forces in such a way that the sum is greater than the parts. The result can be a thoughtful, ethical, and high-quality approach to AI that lifts us to even greater heights.
This article originally appeared in CSA Research.
Scott W. Klein is the president and CEO of LanguageLine Solutions.
