August 18, 2023
In the quest to fulfil the age-old desire of talking to animals, the rise of advanced AI algorithms, particularly Large Language Models (LLMs), has sparked optimism about achieving this seemingly fantastical feat. This ambitious pursuit, coined as the "Doctor Dolittle challenge," has attracted scientific consortia and commercial endeavours aiming to bridge the gap between human and animal communication. Despite the allure of conversing with creatures, several formidable obstacles obstruct this path.
Identifying three primary challenges, researchers acknowledge the complex nature of this endeavour:
Firstly, while AI models can craft animal-like communication samples, deciphering their context remains a daunting task, as human perspective inherently biases interpretation.
Secondly, as AI algorithms strive to discern context autonomously, rigorous controlled experiments are essential to validate whether animals truly respond to AI-generated signals in varying situations. However, the propensity of AI to detect spurious correlations poses a risk.
Thirdly, animal communication largely centres around specific contexts, such as alarm or courtship, limiting the scope of meaningful interaction.
While these hurdles loom large, the allure of employing advanced AI to comprehend and emulate animal communication persists. The "Doctor Dolittle challenge" sets criteria for success in this endeavour, inviting scientists to embark on this mission. Despite AI's capacity to generate animal-like signals, effective communication mandates context comprehension and eliciting appropriate responses, all while navigating the constraints of animal communication modes.
Illustrative examples, such as the honeybee's intricate "waggle dance", underscore the complexities. Although AI can orchestrate robotic interactions that animals respond to in specific scenarios, these instances don't necessarily translate to broader communication achievements. Ultimately, while the "Doctor Dolittle challenge" sparks intrigue and offers opportunities for technological advancement, the profound gaps in comprehension and context remain formidable, evoking the enduring wisdom of philosopher Ludwig Wittgenstein "even if a lion could speak, we could not understand it."
But is this a good or bad thing for animals involved?
AI ethics is a rapidly growing field that is concerned with the ethical implications of AI. While there is a group of sentient beings who are affected by AI, but are rarely mentioned within the field of AI ethics—the nonhuman animals. AI ethics needs to broaden its scope in order to deal with the ethical implications of this very large-scale impact on sentient, or possibly sentient, beings.
Animal welfare is important because there are so many animals around the world suffering from being used for entertainment, food, medicine, fashion and scientific testing. In the context of AI communication with animals, it is important to consider animal welfare because AI could have significant impacts on animals. The impact of research on animals varies from almost insignificant effects on some animals (for instance where nothing more occurs than observation of their behaviour), to major effects on some that undergo very painful or distressing procedures and ultimately death.
On the other hand, what if the animal said "No, I don't want to be part of your AI experiment?"
- AI and the Doctor Dolittle challenge Current Biology
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