The ways animals use and benefit from technology are the focus of our minor in animal-computer interaction. Students can learn how technology can improve the lives and health of animals in the wild, in zoos, on farms, in shelters, or in our homes. This minor will teach you how to put cutting-edge technology to use for core areas of research on animal cognition, wildlife and poacher tracking and monitoring, maker applications for animals, and more.
An ACI minor will introduce the types of research and skills needed for jobs in local, state, federal, and global organizations for wildlife conservation and management; research laboratories; animal-centered nonprofits such as shelters and sanctuaries; zoos and aquariums; livestock care and management; and the commercial pet care industry. It also will teach a suite of valuable technical skills, such as maker applications, app development, data analytics, VR/AR, and more, that are well-suited for a variety of career paths.
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The 15-credit minor in ACI requires five courses, one of which is selected from a list of skill-based courses integral to ACI. Students can start exploring this minor by taking any of the four required courses:
This course provides students with a general introduction to the scientific study of animal behavior, including a broad overview of how developmental, physiological, and ecological factors determine behaviors and the evolutionary forces that shape those behaviors.
What are the origins and computational foundations of intelligence? How close are we to building machines that think like humans and animals? We will explore how cognitive abilities are distributed across the animal kingdom, investigate which abilities are uniquely human, and discuss progress building artificial intelligence that mimics biological intelligence.
This course introduces cutting-edge Animal-Computer Interaction methods with a focus on how they are used to enhance animal welfare, enrichment, husbandry, and cognitive research opportunities. It will also take a critical approach and consider key challenges relating to access, ethics, implementation, scale, and evaluation of ACI methods.
This exploratory seminar is an introduction to ACI. We will draw on faculty- and student-selected readings, multimedia materials, and guest lectures from current ACI practitioners to discuss what we think about the ethics, history, state-of-the-art, and possible futures for this broad field of practice.
Creating technology for non-human animals presents designers with a new challenges and conundrums. The field of human-computer interaction (HCI) has generated numerous methods and toolkits for (human) user-centred design. These extend from interviews and focus groups to creative workshops with Lego and Play-Doh. Unfortunately, few of these methods work well with species that do not share human language and our capacity for speculative, abstract envisioning.
Sarah Webber is a Research Fellow with the Human-Computer Interaction group in the School of Computing & Information Systems. Her research focuses on the design and use of interactive technologies in zoos, for connecting visitors with wildlife and for animal welfare.
Employers are looking for people with a strong grounding in computer science and technical knowledge of animal sciences. You can help fill that unique workforce gap. Prepare to work with sensor technology, large data sets, and predictive analytics, all aimed at improving the health and well-being of production animals and pets.
Animal informatics, including the subfield of animal-computer-interaction, is an applied research program of interest to the pet care industry, captive animal management (e.g. zoos, aquariums, livestock), animal welfare organizations, assistive and therapeutic support animal programs, veterinary medicine, wildlife conservation, and the cognitive, biological, and evolutionary sciences.
From pets to zoo animals we can now provide unique enrichment opportunities for animals, (such as the dog or rhino "Foobler"), and more appropriate interfaces for service animals, such as nose-friendly light switches, as well as assistive technology for animals themselves, including 3-D replacement limbs.
Whether it's tracking & monitoring the movements of deer in Bloomington; diseased or endangered species in Indiana; or the migration patterns of animals throughout the world living on land, in the ocean, or in the air, these technologies include light-as-a-feather sensor design and data capture, the deployment and analysis of video data from drones, and still-image capture and analysis from social media.
By studying how animals learn and think, we can discover which cognitive abilities are shared across the animal kingdom and which abilities are uniquely human. Moreover, by leveraging insights from animal cognition, we aim to build artificial brains with the same power and flexibility as biological brains.
Through studying exhibit design; novel approaches to data collection, analysis, and visualization; simulations and immersive experiences; or even the translation of other species' multisensory forms of communication, technological innovation can help us understand animals and improve our interactions with them in remarkable ways.
The computer-based approach could also be applied to many more chemicals than animal testing, which could lead to wider safety assessments. Due to costs and ethical challenges only a small fraction of the roughly 100,000 chemicals in consumer products have been comprehensively tested.
Animals such as mice, rabbits, guinea pigs and dogs annually undergo millions of chemical toxicity tests in labs around the world. Although this animal testing is usually required by law to protect consumers, it is opposed on moral grounds by large segments of the public, and is also unpopular with product manufacturers because of the high costs and uncertainties about testing results.
A study led by scientists at Johns Hopkins Bloomberg School of Public Health suggests that advanced algorithms working from large chemical databases can predict a new chemical's toxicity better than standard animal tests. The computer-based approach could replace many animal tests commonly used during consumer product testing. It could also evaluate more chemicals than animal testing, a change that could lead to wider safety assessments.
For the study, which appears online today in the journal Toxicological Sciences, the researchers mined a large database of known chemicals they developed to map the relationships between chemical structures and toxic properties. They then showed that one can use the map to automatically predict the toxic properties of any chemical compound more accurately than a single animal test would do.
Owing to costs and ethical challenges, only a small fraction of the roughly 100,000 chemicals in consumer products has been comprehensively tested. Mice, rabbits, guinea pigs, and dogs annually undergo millions of chemical toxicity tests in labs around the world. Such testing is opposed on moral grounds by large segments of the public and, given its high costs and the uncertainties about the testing results, it is also unpopular with product manufacturers.
The most common alternative to animal testing is a process called read-across, in which researchers predict a new compound's toxicity based on the known properties of chemicals that have a similar structure. Read-across is much less expensive than animal testing, yet requires expert evaluation and somewhat subjective analysis for every compound of interest.
As a first step toward optimizing and automating the read-across process, Hartung and colleagues two years ago assembled the world's largest machine-readable toxicological database. It contains information on the structures and properties of 10,000 chemical compounds, based in part on 800,000 separate toxicology tests.
"There is enormous redundancy in this database," Hartung says. "We found that often the same chemical has been tested dozens of times in the same way, such as putting it into rabbits' eyes to check if it's irritating."
This redundancy, however, gave the researchers information they needed to develop a benchmark for a better approach. The team enlarged the database and used machine-learning algorithms, with computing muscle provided by Amazon's cloud server system, to read the data and generate a "map" of known chemical structures and their associated toxic properties. They developed related software to determine precisely where any compound of interest belongs on the map and whether, based on the properties of compounds "nearby," it is likely to have toxic effects such as skin irritation or DNA damage.
The most successful version of the toxicity-prediction tool the team developed was on average about 87 percent accurate in reproducing the consensus of animal test results across nine common tests. By contrast, the repetition of the same animal tests in the database was only about 81 percent accurate. In other words, any given test had only an 81 percent chance, on average, of obtaining the same result for toxicity when repeated.
The U.S. Food and Drug Administration and the Environmental Protection Agency have begun formal evaluations of the new method, to test whether read-across can substitute for a significant proportion of the animal tests currently used to evaluate the safety of chemicals in foods, drugs, and other consumer products. The researchers are already using the tool to help some large corporations, including major technology companies, determine whether they have potentially toxic chemicals in their products.
The Department of Animal and Avian Sciences provides a challenging program for academically talented students interested in the application of biology and technology to the care, management and study of domestic and aquatic animals. In addition to emphasizing the traditional farm species of dairy and beef cattle, sheep, swine and poultry, our program includes options for courses in equine science, animal biotechnology, and sciences which prepare students for veterinary or graduate school. Animal sciences majors explore a wide range of subjects - from fundamental biology to animal nutrition, physiology and genetics - while integrating science and economics into animal management. Courses offered by this department may be found under the following acronym: ANSC 152ee80cbc
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