AI and Animals Wiki

Collection of AI & Animals news articles, updated weekly

In Veganomics magazine, from Open Paws

by Max Taylor

by Andrea Owe & Seth D. Baum, published by AI and Ethics in 2021

IAA’s wiki of prompts for advocates

by Leonie N. Bossert, published by Technology in Society Journal in 2021

by Lewis Bollard, Open Philanthropy farm animal welfare research newsletter

by Brian Kateman, Forbes

by Simon Coghlan & Christine Parker, published by Springer Link in 2023

by Leonie N. Bossert, published by Springer Link in 2023

by Sankalpa Ghose, Yip Fai Tse, Kasra Rasaee, Jeff Sebo, Peter Singer

by Peter Singer & Yip Fai Tse, published by Springer Link in 2022

by Thilo Hagendorff, Leonie N. Bossert, Yip Fai Tse & Peter Singer , published by Springer Link in 2022

by Soenke Ziesche, published by Philosophies Journal in 2021

by Oliver Bendel, published by Paladyn, Journal of Behavioral Robotics in 2018

by Scherrer et al., 2023

by Max Taylor

by Constance Li, Nicholas Kees Dupuis

by Adrià R. Moret

by Sam Tucker

by Rethink Priorities, Tapinder Sidhu

by Elijah Persson-Gordon

AI Ethics: Global Perspectives

Peter Singer, BigThink

Constance Li, Generation Vegan

Vegan Hacktivists and Plant Based News

Farm Forward and Faunalytics

New Harvest and Schmidt Futures

Our Hen House podcast

Tim Ferriss

How I Learned To Love Shrimp podcast

guide by Steven Rouk

Look inside the page

Sofia Balderson

Kyle Behrend

February 15 2024, Food Dive

SF Hardware Collective

4-8 December 2023, in Raleigh, NC, USA - small and more academic, not as much about industry

4-5 October 2023 in Princeton, NJ - academic and philosophical (see notes)

on Forbes by Brian Kateman

personal blog by Steven Rouk

By Tobias Baumann, Center for Reducing Suffering

by Michael Dello-Iacovo, Sentience Institute

By Tobias Baumann, Center for Reducing Suffering

by Jacy Reese, in Futures

by Abraham Rowe

by Jacob Eliosoff

by Michael Aird

by Yip Fai Tse

by Zachary Cosenza & Michael Todhunter, published by New Harvest in 2022

by Dorota Owczarek in Nexocode

by Emma Penrod

by AI for Animals

by Suresh Neethirajan (in Frontiers in Veterinary Science)

by Sentient Media

by Digital Journal

by Stray Dog Institute

by Daniel M Weary (in Technology in Society)

by Tuyttens et al (in Frontiers in Veterinary Science)

1. Merck Global company based in US with a department for Animal Health Intelligence that has multiple products that incorporate AI for monitoring systems in livestock farming, aquaculture, and pets. 2. Connecterra Dutch company with global reach and many corporate partnerships that developed a collar mounted device for dairy cows for monitoring animal health and methane emissions. 3. Vencomatic Group Global company based in The Netherlands with tech for autonomous broiler chicken housing and egg handling that has some AI integration 4. Cainthus US company using AI video monitoring system for managing dairy herds 5. Animals.ai Swedish startup developing AI video monitoring system for managing dairy cow herds 6. AI4Animals Dutch startup using AI monitoring system for slaughterhouses 7. Farmsee ****Israeli startup using AI to monitor growth of pigs 8. OneCup AI Canadian startup using AI to monitor for cow ranching herds 9. Beakbook London tech startup using AI to support the poultry industry

by Rethink Priorities, Tapinder Sidhu. Case studies were in regards to computer vision and include: ◦ Placing them near wind turbines which shut them off when birds are detected, resulting in a 75%-89% reduction in eagle fatality rates. ◦ Installing them in crop fields to scare off birds when they approach (prevents stimulus acclimatization) to reduce the need for lethal methods of deterrence.

by Robin McKie. AI wildlife monitoring “provides important benchmarks for measuring biodiversity in future… In the past, we have had to estimate local wildlife populations from the dead animals – such as badgers – that have been left by the track or the roadside. This way we get a much better idea of population sizes.”

by Max Taylor

AI is increasingly being used in fisheries to improve efficiency and product quality, from stock assessments and bycatch monitoring to onboard processing systems. Companies like Carsoe are incorporating AI and machine learning to optimize processing steps and standardize product quality across vessels, while firms like ThisFish are using AI for supply chain traceability and quality control. These technologies aim to boost profits by enhancing fish quality and reducing operational inefficiencies, with potential benefits in both at-sea and land-based seafood processing.

A research team led by Michigan State University has received a $1 million grant to develop AI-driven solutions to monitor piglet and sow behavior, aiming to reduce piglet preweaning mortality. The project uses computer vision to track piglet nursing patterns and teat function, providing data to improve husbandry practices and support research in areas like animal welfare and nutrition. The findings will help standardize practices and enhance piglet survival rates, with the potential for broader application across the pork industry.

Fortifi’s partnership with Völur uses AI to analyze data from automated meat processing equipment in real time. The AI optimizes cutting and processing by adjusting decisions based on inventory levels and the specific characteristics of each carcass. This ensures that each cut maximizes meat yield, reduces waste, and lowers the environmental impact by improving efficiency and minimizing CO2 emissions during production.

MarineSitu develops rugged, low-cost marine monitoring systems using advanced cameras, sonar, and machine learning to improve biomass estimation and health monitoring in aquaculture. Their technology is designed for harsh marine environments, and they are expanding into aquaculture with support from government grants and investment from Hatch Blue's accelerator program.

Precision livestock farming holds significant promise for improving animal health, efficiency, and environmental sustainability, but adoption is hindered by economic risks and limited commercial availability. Farmers are hesitant to invest in these technologies without clear evidence of a return on investment, and the complexity of some precision systems further complicates their implementation. Additionally, data ownership remains a contentious issue, with producers concerned about who controls the valuable data generated by these systems and how it is used.

Precision livestock farming holds significant promise for improving animal health, efficiency, and environmental sustainability, but adoption is hindered by economic risks and limited commercial availability. Farmers are hesitant to invest in these technologies without clear evidence of a return on investment, and the complexity of some precision systems further complicates their implementation. Additionally, data ownership remains a contentious issue, with producers concerned about who controls the valuable data generated by these systems and how it is used.

Summary: The Ulangizi app, piloted by Opportunity International, leverages AI to assist Malawian subsistence farmers by providing crop and animal disease management advice in the local language, Chichewa, through WhatsApp. For example, farmers can take photos of sick animals, and the app diagnoses issues and suggests treatments, helping prevent livestock losses. Despite challenges such as limited smartphone access and connectivity, the app is seen as a valuable resource, saving time and money by providing quick, reliable agricultural information.