Using AI With EY For A More Sustainable Future
Are you passionate about artificial intelligence? Are you, like millions of people, concerned about the effects of climate change? How about harvesting data to contribute to a more sustainable future?
EY extends its data-driven sustainability mission in an enriching and rewarding journey with generous prizes.
For the third consecutive year, university students and early-career professionals globally are offered the opportunity to contribute towards saving the planet!
This is done in the form of a hands-on challenge, the ‘Open Science Data Challenge’, where participants use satellite data to construct machine learning models to help address real issues related to building a more sustainable world, such as fighting natural disasters, preserving biodiversity and combating famine caused by climate change.
The challenge annually attracts thousands of participants across the globe to use their machine learning skills to solve some of the world’s most pressing issues.
The sustainability agenda is at the heart of EY’s purpose of being. In fact, EY has been named as a leader in Environmental, Social and Governance (ESG) and Sustainability Consulting in 2022, by research and advisory firm Verdantix.
Without a doubt, ignoring sustainability, environmental and climate change risks is no longer an option. That’s why EY’s multidisciplinary teams support organizations in understanding the risks and opportunities arising from global phenomena while creating strategies that help them to navigate challenging times.
Following COP26, the UN’s Climate Change Conference, hundreds of financial institutions made net zero commitments especially since companies who fail to act responsibly may be exposed to climate-related risks.
Building on this, EY follows a structured programme to reach its own sustainability goals that include the introduction of nature- and science-based projects offsetting the amount of carbon that is emitted by the organization every year.
EY has invested heavily in the growing field of Artificial Intelligence. Teams approach the adoption of AI and Intelligent Automation in a human-centered, pragmatic, results-focused and ethical manner in to get the best possible value and return on investment.
In today’s world where technology, especially AI, is being used in all fields of industry to optimise and automate operations, its development also acts as one of the main drivers towards achieving sustainability goals and as a contributing factor towards monitoring natural phenomena to mitigate climate change and to develop more sustainable energy systems.
For many years EY has done its part with a data-driven approach where it has strived to support organisations in data mining and analytics to achieve operational excellence and to steer strategic and tactical decision-making towards a more sustainable path.
Machine learning-based solutions offer a unique approach that can support more complex business problems and EY has been leveraging best practices in contexts, like data analytics, to bring out additional industry insight to support decision-making.
On a local level EY’s technology consulting team actively supported the development of the Malta National AI Strategy. Released in October 2019, the strategy aims to pave a way for Malta to grow strategically in the global economy whilst establishing itself as a leader in the AI space.
This year’s Data challenge revolves around the deeper understanding of rice yield in Vietnam. According to the World Health Organisation more than 800 million people regularly go to bed hungry with numbers increasing steadily year after year.
Being one of the largest global producers of rice, Vietnam is one of the most vulnerable countries to climate change where both the amount of land available for rice and yearly yield growth rates are in decline.
Due to the increase in temperature, change in rainfall patterns, upsurge in frequency of extreme events and rise in sea levels, predicting rice yield could be instrumental to farmers and local communities to maximise their efforts to grow more rice smartly and more efficiently, while increasing the survival rate of millions of people whose lives depend on this type of food.
A past initiative with a plantation company, saw EY support their growth with the incorporation of a data-driven intelligent platform that improved their approach towards meeting customer demands and sustainability targets.
Through the application of machine learning and operations systems data, production simulations and improvements recommendations were made possible, which aided management with a substantial reduction in unnecessary inventory and operating expenses.
And now we are offering you the chance to make a difference!
This year’s challenge answers the key question: can we use AI to make rice production more sustainable?
Machine learning models developed by participants should identify irrigated areas and to forecast rice yield in a given time period using geolocation data from Sentinel 1 and Sentinel 2 satellites provided by our alliance partner, Microsoft’s Planetary Computer.
The best resulting models will win a sizeable amount of prize money but, more importantly, will be provided as open-source for practitioners and environmentalists to be adapted in real-life scenarios.
EY invites participants to contribute to a more sustainable future by registering online on challenge.ey.com
Once registered participants will be provided with all the datasets and domain information together with comprehensive guides and tips on how to accomplish the objectives of the challenge.
This is your opportunity to building a better and more sustainable working world with EY.
EY Consulting teams support organizations to fully draw business benefits from AI adoption through a comprehensive suite of services that include strategy design, data-centric architecture, systems integrations, program operations and cyber risk services, combined with their domain and sectoral knowledge. AI-related consultation services can cover multiple dimensions such as robotic process automation (RPA), data analytics and engineering, MLOps, AIOps, digital transformation, cloud-based Software-as-a-Service, Platform-as-a-Service and Infrastructure-as-a-Service managed deployments. Contact Patrick Bezzina on [email protected] to see how EY can help you reach your organisation’s goals through AI.
Will you be participating in the challenge?