In a groundbreaking development in the field of genetic engineering and de-extinction, Colossal Biosciences has announced the creation of genetically engineered proxies of the long-extinct dire wolf. Unlike a direct resurrection, these proxies are grey wolves modified to exhibit certain traits reminiscent of their prehistoric counterparts. This move has sparked renewed interest in the ethics surrounding de-extinction, prompting discussions about the implications of such scientific endeavors.
On April 17, 2025, the narrative surrounding this ambitious project took a significant turn when the capabilities of AI were brought into play. Google’s advanced language model, Gemini 2.5, was employed to analyze the ethical dimensions of de-extinction. The model utilized its 'Deep Research' feature to sift through hundreds of web sources, ultimately synthesizing a comprehensive report that spanned an impressive 12,000 words and included 93 un-hallucinated references.
The report not only detailed the scientific aspects of creating dire wolf proxies but also delved into the ethical considerations that accompany such innovations. Key ethical issues identified included animal welfare, ecological risks, restorative justice, and moral hazards associated with manipulating nature. The analysis provided a nuanced view of the potential consequences of these actions, emphasizing the need for careful consideration of all stakeholders involved.
Building on the initial findings, Gemini 2.5 was further tasked with conducting a detailed ethical analysis, which resulted in a 5,000-word document. This analysis followed a structured workflow that included defining the subject, identifying stakeholders, and evaluating alternatives. One of the standout features of the analysis was its ability to articulate complex ethical dilemmas, such as weighing the predictability of animal suffering against the uncertain benefits of ecological restoration.
The analysis produced a table evaluating various alternatives to the creation of dire wolf proxies, using both consequentialist and deontological frameworks. For instance, one option was to halt the project altogether and redirect resources towards more effective conservation efforts. This alternative was deemed to have a likely high positive net utility, as it would avoid animal suffering and ecological risks while redirecting resources to potentially more effective initiatives.
Another alternative involved refocusing on proxy research with enhanced ethical oversight, which could mitigate some negative outcomes while still incurring welfare costs. A third option suggested shifting to non-animal methods altogether, which would eliminate the ethical concerns of animal suffering and ecological risks, but would sacrifice certain unique knowledge that can only be obtained from live organisms.
As the analysis progressed, it became clear that the ethical implications of creating proxies are complex and multifaceted. The recommendations generated by Gemini 2.5 were tailored for key stakeholders, highlighting the importance of a governance framework that ensures responsible innovation in biotechnology.
This exploration of de-extinction through the lens of AI raises significant questions about the future of research practices. The author noted that language models like Gemini 2.5 are rapidly becoming capable of automating core research tasks such as literature reviews and synthesizing complex arguments into coherent reports. This evolution in AI technology could fundamentally reshape how researchers approach their work, particularly in fields that require ethical scrutiny.
Moreover, the insights gained from this analysis may prompt a broader discussion about the role of AI in research and its implications for human expertise. As AI tools become more integrated into academic and scientific discourse, the need for researchers to develop a clear vision and articulate their methodologies in plain language becomes increasingly critical.
In a parallel development, the language profession is also grappling with the implications of AI technology. John Worne, CEO of the Chartered Institute of Linguists (CIOL), recently discussed the mixed experiences of language professionals with AI tools. He highlighted the findings of a UK House of Lords inquiry that emphasized the risks associated with AI in language services, particularly for low-resource languages.
Worne pointed out that while some members of CIOL have embraced AI tools, others remain skeptical due to concerns about quality and trust. He raised important questions about how generative AI might influence language use and shape cultural identity. Worne noted that language is a “human meta skill,” encompassing not just communication but also identity, culture, and belonging.
Looking ahead, Worne expressed cautious optimism for the next generation of linguists, suggesting that digital natives may be better equipped to leverage AI creatively and multitask across various tools. CIOL plans to expand its free resources and community engagement in 2025, ensuring that the future of language work remains inclusive and informed by genuine human insight.
In another realm of AI development, researchers have been assessing the reasoning abilities of large language models through a benchmark known as the Reasons benchmark. This benchmark evaluates how well AI models can generate accurate citations and provide understandable reasoning. Recent comparisons between DeepSeek’s R1 model and OpenAI’s o1 model revealed significant performance differences, with OpenAI’s offering outperforming DeepSeek in terms of citation accuracy and reasoning quality.
The testing involved a dataset of 4,100 research articles across topics related to human cognition and computer science. OpenAI’s o1 model demonstrated a lower hallucination rate and higher accuracy compared to DeepSeek’s R1, highlighting the competitive landscape of AI development. These findings suggest that while AI tools are advancing rapidly, there remains a critical need for researchers to verify the information provided by these models.
The intersection of AI technology with de-extinction efforts, language services, and research practices underscores the transformative potential of these tools. However, as both Colossal Biosciences and language professionals navigate this evolving landscape, the ethical considerations and implications for human expertise must remain at the forefront of the conversation.
