Smart technologies such as those in the Machine Intelligence family – including Artificial Intelligence and Machine Learning – undoubtedly have great potential to deliver social benefits. A recently published article from Harvard Business Review discusses how smart technologies can help and are helping nonprofit organizations be more efficient in executing their missions. In a recent discussion Stanford Graduate School of Business professor, Susan Athey, points out that while in the past smart technologies were pretty expensive to acquire, today, with a lot of the technical tools being open source and easier computing power access via cloud, even small organizations can leverage Machine Intelligence.
Taking a closer look into the current use of Machine Intelligence in the nonprofit sector, it becomes evident that the common application areas are in the realm of operation improvement. We, at MI4People, want to complement those use cases with projects that serve the main ambitions of NPOs in delivering Public Good.
The first MI4People’s projects are just starting, and our team of volunteers is working hard to ensure that they move forward. But in addition to the great commitment of the volunteers, we also need your financial support.
Our running and planned projects aim to fight hunger, improve healthcare in developing countries, and make wildlife conservation efforts more effective. Because of the nature of the problems we are targeting, our projects are complex and multi-phased – their total durations can extend over several years. Therefore, we must ensure that the management and organization of the individual projects is taken over by permanently employed Machine Intelligence experts who can fully focus on the research at MI4People. The financing of their salaries and other running costs is ensured through your donations.
That is why we have now started our first fundraising campaign on betterplace.org. There are also other options for donating on our website. Give us your support by looking at our detailed call for donations below and/or by sharing it with your network.
MI4People could not exist without your contribution! We remain very grateful to you for your support!
Together, we can build a better world, for all of us!
Your MI4People Team
Call for donations on betterplace.org: https://www.betterplace.org/en/projects/103032-mi4people-empowering-public-good-with-machine-intelligence
Alternative donation options on our website: https://www.mi4people.org/donations
As Germany transitions into its post-Merkel chapter, the new coalition government laid out several high-level ambitions and policies last month (see, for example, “Coalition Agreement 2021-2025) with strong positive slogans like “We are not interested in a policy of the lowest common denominator, but rather a policy of great impact. We want to dare to make more progress. – Olaf Scholz (German Chancellor)”. There were many statements of direction given in the coalition agreement that relate to high-tech that focus on digital themes including investment in AI and data technologies and regulations along with digital identity, circular economy, sustainability, digital in agriculture, eHealth, and so on (see also an analysis by Carsten Stoecker, CEO/Co-Founder of Spherity GmbH).
The new government also wants to push for FinTech and crypto leadership for Germany, EU-wide fair digital markets, and quantum computing. With a stated mission to reduce bureaucracy and embrace high-tech, one can hope to see higher level of digital transformation in Germany as the operation of the new government takes hold.
AI/ML-powered image analysis continues to help in detection and treatment of many severe illnesses.
For example, 2/3rd of a million women around the world die each year from breast cancer. As a November/2021 article from World Economic Forum points out, in third world countries like India (where 90 thousand breast-cancer deaths occur annually) a key cause of fatality is the lack of early detection facilities and expertise. As described in the above World Economic Forum article, innovative use of radiation-free thermal imaging with AI/ML based analysis (see, e.g., Thermalytix) is now able to create an effective breast cancer detection technique without the need of heavy radiology equipment and advanced radiologists thus providing life-saving help to women in poorer and remote country locations.
Medical technologies based on Machine Intelligence, once proven in the diagnosis and treatment of a set of diseases can also be quickly extended to other related ailments. A good example, particularly relevant in the current COVID pandemic, is described in a Microsoft AI related news article published earlier this year. The X-Ray + AI system from a South Korean medtech company Lunit was originally designed to detect some ten other diseases from chest X-rays and was quickly adapted and extended to detect the presence and severity of COVID infection thus improving patient’s prognosis and curtail transmission.
From Nature Conservation
Over 2/3rd of our planet is occupied by oceans which help us survive well on land in many ways including producing half the oxygen in and absorbing about a quarter of carbon emission from our atmosphere. Thus, a better understanding and protection of oceans are critical for human well-being. With the use of underwater sensors and AI-powered data analyses, scientists at LoVe Observatory of Norway are generating real-time physical, biological, and chemical data from the sea and then using it to improve ocean conservation, and helping researchers to better understand the impact of human-created pollution and consequences of climate change on key ocean properties.
The concept of ‘digital twin’ i.e., a digital/virtual representation of a physical object or process, is not new anymore and is being used in many industry sectors, especially, in the engineering world. However, an ambition to create a digital twin of our planet to fight climate change is quite a novel one. This program is called Earth-2 and “… will employ three technologies to achieve ultra-high-resolution climate modeling: GPU-accelerated computing; deep learning and breakthroughs in physics-informed neural networks; and AI supercomputers—and a ton of data”. The goal of Earth-2 is to encourage all concerned to use comprehensive and higher-quality data to better protect our environment and predict/remediate the adverse consequences of extreme climate events.
Given the huge power and potential of Machine Intelligence (MI) technologies, their application for Public Good is not surprising. As the cited examples in this newsletter show, MI-based medical technologies are saving lives and helping us better protect our environment. Since nonprofit organizations engaged in the delivery of Public Good are often quite small, they need help from both private and public sector to adopt and utilize such technologies to better deliver their stated missions. In particular, digital transformation agenda of modern governments must make key contributions in this area with suitable financial programs directly supporting MI adoption in the nonprofit sector, and with regulations and incentives to encourage large private sector enterprises to do the same.