This is an email from AI and Global Grand Challenges, a newsletter by Nural Research.
Welcome to Nural’s newsletter where we explore how AI is being used to tackle global grand challenges.
In this newsletter you will find a compilation of articles, news and cool companies all focusing on using AI to tackle global grand challenges.
Packed inside we have:
- An exploration of how AI is being mobilised by GCHQ in intelligence gathering initiatives.
- A data driven approach to tackling overfishing — by Nathan Thomas
- YouTube taking down a chess video because the references of “black” and “white” were flagged as hate speech
- and more…
Nural Article — OceanMind — A data-driven approach to tackling overfishing
Overfishing is one of the most significant drivers of the decline in oceanic biodiversity across the world. It occurs when vessels catch fish faster than fish stocks can replenish (reproduce). 1 in every 5 fish sold is caught illegally, where these illegal catches amount to $23.5 billion…
Fortunately, OceanMind aim to solve this problem. OceanMind is a non-profit which uses satellites and artificial intelligence to reduce the level of unregulated overfishing. It achieves this by working with governments and local authorities to identify non-compliant action in the seas…
Key recent developments
What: GCHQ, the intelligence agency for the UK, have published a report which outlines the ways they will be using AI to ensure public safety. These include tackling areas like child sex abuse, disinformation and trafficking.
Key Takeaway: The use of AI in intelligence gathering comes at no surprise as the potential of this technology is evident. Beyond the specific application areas in the report, the document also offers useful governance approaches such as exploring three stages of fairness: data fairness, design fairness and outcome fairness. These frameworks for AI ethics are useful for all industries.
What: At a time when we are still trying to determine the contexts where we should and shouldn’t be using AI, lawmakers in the US have unanimously voted to tightly restrict local police use of facial recognition technology.
Key Takeaway: Governing the use of AI in critical areas such as policing is essential. In last week’s newsletter, we saw the adverse effects of Uber’s facial recognition tech that underperformed on non-white drivers. The added dangers of attacks that can deceive facial recognition technology means that this vote has come at a great time.
What: Africa has the world’s fastest growing population and this growth is bringing increased energy demands. However, meeting the energy demands in a way that is compatible with global decarbonisation is often difficult. Fortunately, a company named Africa 365 is leveraging AI to bring renewable energy to 100 million people living in communities without access to national grids.
Key Takeaway: Approaches such as those by Africa 365 are bringing data based certainty to potential green investors and help to facilitate the growth of green energy supply via microgrids. It is also spurring an open approach to sharing energy data which can benefit people globally.
Other interesting reads
Cool companies I have come across this week
Paige — Paige build AI-based digital diagnostics delivered via an interoperable enterprise imaging platform. They also empower life sciences companies to evaluate treatment options for patients and design new biomarkers.
AI, People & Planet — AI, People & Planet is a research initiative that explores how rapid technological change like artificial intelligence (AI) might both support and undermine transformations to sustainability.
AI/ML must knows
AutoML — The process of automating the process of applying machine learning to real-world problems. AutoML covers the complete pipeline from the raw dataset to the deployable machine learning model.
Statsmodels — Python package for ML and statistics
Tensorflow/keras/pytorch — Widely used machine learning frameworks
Generative adversarial network — Generative models that create new data instances that resemble your training data. They can be used to generate fake images.
Deep Learning — Deep learning is a form of machine learning based on artificial neural networks.
Nural Research Founder