• Audience
    Secondary school
  • Learning stage
    Stage 4, Stage 5

IBM EdTech Youth Challenge projects to help reduce consumption and degradation of natural resources, and the effects climate change is having on our world.

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Please note: entries to the IBM EdTech Challenge have now closed. The winning teams will be announced on Friday 12 November 2021.



Many of the Earth's resources are being depleted faster than they can be renewed. This means that we are living in an ecologically unsustainable way. In order to support environmental sustainability and conserve Australia's biodiversity, we will have to embrace new and sometimes quite radical management practices of Earth's resources.

How can we use AI and design thinking methodologies to produce solutions that can help achieve ecological sustainability?

Watch and read the information and definitions below to learn more about sustainability and how it is linked to biodiversity and climate change to define your IBM EdTech Youth Challenge project problem to solve. The United Nations Sustainable Development Goals are an ideal starting point to looking at local problems within a global context of sustainability issues. Citizen science projects Wildlife Spotter and Australasian Fishes Project are project case studies and resources that may also inspire and encourage you to think about possible environmental sustainability research to focus on. There are also examples of potential applications of AI in citizen science which can be used for brainstorming innovative ideas for AI applications to address environmental sustainability problems. Information on next steps of the challenge and additional resources will help guide and inspire the focus of your IBM EdTech Youth Challenge project on environmental sustainability concerns in your local community and beyond.



AI and design thinking for environmental sustainability


Image classification in citizen science


Citizen Science programs provide a crucial source of data about biodiversity and the effects of climate change on ecological sustainability. It relies on public participation in scientific research to help us to gain insights into our environment and create additional data sources.

Wildlife Spotter and Australasian Fishes Project are some examples of image classification projects that rely on citizen scientists to classify images according to taxon/species. These projects present many opportunities for technologies such as AI to make even more significant contributions. Below you will find examples of potential applications of AI in citizen science which can be used as a great starting point to inspire and encourage you to brainstorm further innovative concepts.


Project case study: Wildlife Spotter


Australian Museum's DigiVol’s Wildlife Spotter is an image-processing platform to support the tagging of thousands of images of wildlife, and their behaviours, taken by camera traps. In 2020, citizen scientists have transcribed over 2.4 million animal identifications in images on DigiVol's Wildlife Spotter. This vital information will help Australian researchers monitor and protect Australia's iconic wildlife.

How does it work?

Each Wildlife Spotter project outlines a set of tasks to be completed by citizen scientists. The data submitted will provide insights that can feed directly to conservation management. Contributors learn how to:


  • ID animals and tag the images

    Identification guide on how to ID the animals with a list of key features and images.

  • Identify the animal/s on each image

    Identify animal/s in each image by matching them to a specified list. Images are captured in bursts of three so citizen scientists can look at the movement of the animal/s to help identify them. You can skip the image if you don't know what the species is.

  • Choose the number of individuals

    Count the number of animals in the image. If there is more than one type of animal, then select the additional animal and indicate the number.

  • Add notes to anything to anything of interest

    Add notes of an unlisted animal that you know the common name of.


Project case study: Australasian Fishes Project


Australasian Fishes Project

The Australasian Fishes Project on iNaturalist is a citizen science project that creates an extensive 'image library' to identify fishes, map their distributions and investigate changes in growth.

The project is a collaboration between the public, industry partners and professional ichthyologists at a number of Australian and New Zealand museums and other fish-related institutions.

This crucial data gives us insights into the impacts of climate change such as coral bleaching and its effect on marine biodiversity and health.

How does it work?

The Australasian Fishes Project is a community based project that allows anyone to upload images of their observation and share it. Other members of the community can also help identify your observation if you are unsure of certain fields. For research quality observations that can be used for science, submissions require all fields outlined below.


  • Who you are

    You will need to make an iNaturalist account to post your personal observations.

  • What you saw

    You can identify what you saw. If you capture a photo, you can leave this field blank and the community can help.

  • Where you saw it

    Record the coordinates of the encounter.

  • When you saw it

    Record the date of your encounter.

  • Evidence of what you saw

    Upload clear photos of your observation and include different angles. The community can help add, improve or confirm the identification of the organism you encountered.


Role of AI in citizen science


Advances in AI technologies that allow computers and machines to function in an intelligent manner are now being applied in citizen science.

Paul Flemons (Manager of Citizen Science at the AM), discusses whether AI is a threat to Citizen Science and explores the opportunities and risks that it presents. A recent publication that he co-authored, looks at how AI is already influencing this field through a range of technologies that assist/replace humans in completing tasks, influence human behaviour and improve insights into data.

Citizen science projects that use image based classification systems to identify animals have great potential for AI application. Some examples of possible applications are outlined below to serve as a springboard for further brainstorming ideas.


How AI can assist in citizen science
Task Example
Classifying images AI can be used in image classification such as species identification.
Filtering out repetitive and mundane tasks AI can be used to speed up and filter out repetitive and mundane tasks eg. filtering out images that don't have animals. This allows citizen scientists to focus on work that is more interesting or requires further knowledge and expertise.
Digitisation (converting information into a digital format) of biodiversity research AI can help digitise biodiversity research through identifying and sorting museum specimen labels.

Source:

Ceccaroni, L., Bibby, J., Roger, E., Flemons, P., Michael, K., Fagan, L. and Oliver, J.L. (2019) Opportunities and Risks for Citizen Science in the Age of Artificial Intelligence. Citizen Science: Theory and Practice, 4(1), p.29. DOI: http://doi.org/10.5334/cstp.241



Atlas of Living Australia

The ALA is Australia’s one-stop-shop for information on our diverse wildlife: you can look up facts, explore species in your area, and view images of species in the wild and specimens in museums.

Search ALA Data

Next steps

Register to participate in the IBM EdTech Youth Challenge and review the Project Guide and Project Logbook. Follow the Project Guide steps to identify issues around health concerns and how AI technology and design thinking can be applied.


  • Problem identification

    Describe a local environmental sustainability problem.

  • Knowledge of AI

    Is there an AI solution to assist in solving this problem?

  • Understanding the user

    Who will benefit from the solution and how.

  • Brainstorm solutions

    Document how creative and critical thinking were used to brainstorm, with one solution being prioritised.

  • Data

    Identify potential data sources, and investigate a data sample and privacy issues.


Additional resources

Websites:



Film:



Podcasts:



Books:


  • People on Country: Vital Landscapes, Indigenous Futures

    Jon Altman and Seán Kerins (2012), Indigenous Futures, Sydney: The Federation Press.

  • The Future We Choose: Surviving the Climate Crisis

    Christiana Figueres and Tom Rivett-Carnac (2020), London: Manilla Press.

  • Sunlight and Seaweed: An Argument for How to Feed, Power and Clean Up the World

    Tim Flannery (2019), Melbourne: The Text Publishing Company.

  • The Climate Cure: Solving the Climate Emergency in the Era of COVID-19.

    Tim Flannery (2020), Melbourne: The Text Publishing Company.

  • 2040: A Handbook for the Regeneration

    Damon Gameau (2019), Pan Macmillan Australia.

  • Drawdown: The Most Comprehensive Plan Ever Proposed to Reverse Global Warming

    Paul Hawken (2017), Penguin Books, UK.

  • How to Talk About Climate Change in a way that Makes a Difference

    Rebecca Huntley (2020), Sydney: Murdoch Books.