Much is spoken about the wonderful potential that Artificial Intelligence (AI) has and how it can benefit our lives. However, many are not sufficiently informed and educated in this area to allow them to consciously weigh the pros and cons this technology already brings to their lives. Nowadays, we see how users, tired of endless legal notices and privacy policies, hand over their personal data without knowing who is going to use them and how. What is the result? A lack of trust in AI systems and a fear of the unknown.
This series of Artificial Intelligence 101 articles intend to give the reader a general picture of the current regulatory framework (or lack thereof) around this technology as well as to put the focus on its potential for both helping society and jeopardizing it and, in the latter case, specifically focusing on its discrimination and privacy-related risks.
Artificial Intelligence 101 is mainly divided into ten chapters, including:
The Best of AI—Positive Social Impact
Artificial Intelligence 101: The Best of AI—Positive Social Impact
Despite the risks involved with the use of AI, it is worth noting that AI is potentially beneficial to society. Thus, it is worth understanding and using so that we can improve our quality of life. Decisions made by AI systems are potentially better than those without an empirical basis. In this article, the last of the 101 series about AI, the reader will find some projects that use AI for social good, i.e., a peek at the good impact that AI can have in our lives.
To date, the sectors that are implementing AI systems are progressively increasing. The implementation of AI systems is predominant in the health and food, environment, public and social sector, security and justice, and humanitarian crisis management sectors. Some specific examples of it are:
1. Systems for identifying victims of sexual exploitation:
At Thorn, an international organization focused on combating human trafficking, they work with a combination of facial recognition and human identification technology, social network analysis, natural language processing, and analytics to identify victims of sexual exploitation on the Internet and the dark web. Thorn works with companies such as Google, Microsoft, and Facebook and has helped in identifying 17,092 child victims of human trafficking in the past four years.
2. Systems that enhance economic growth in vulnerable sectors:
AI can be used to detect plant damage through low-altitude sensors (smartphones or drones) to improve the performance of small farms. Microsoft's Azure FarmBeats project is working on this project to enable small farmers to optimize their resources.
3. Systems that help people and businesses to qualify for bank financing:
Companies such as CreditVidya or ZestFinance use alternative data collected through users' smartphones, the Internet, and social networks to generate a predictive model of creditworthiness. There are clear risks involved with these types of AI systems to determine a person's creditworthiness. You can check the article Artificial Intelligence 101: Let’s Talk About Bias (Part I) for more information about the risks of bias. Nevertheless, these AI systems have proved beneficial for people to access micro-loans or grants to start or maintain their local projects.
4. Systems that help manage humanitarian or environmental crises:
There are certain AI systems that use satellite data to monitor and track forest fires, optimize fire management by foresters and firefighters, and alert them if the risk of their exposure increases. For example, following Hurricane Harvey in 2017, the collaboration between Planet Labs (a satellite imagery provider) and CrowdAI provided immediate images of Houston which enabled the detection of road damage caused by the hurricane and a rough quantification of structural damages. Drones with sufficient power can help locate missing persons in hard-to-reach areas, facilitating search and tracking efforts.
5. Systems that help people with special needs:
Applications such as Microsoft's Seeing AI, offer users navigational assistance through their smartphones. The application identifies texts and objects and converts them into digital texts that can be played aloud, contributing to a better quality of life for people with visual impairments.
6. Systems that contribute to identifying and detecting diseases:
In the health sector, some studies indicate that, with deep learning, AI systems would be able to detect some types of cancer (like skin cancer) early with greater accuracy than humans. Nature magazine published in December 2021 the results of tests undertaken by experts in this regard:
"Recent researches have used artificial intelligence to classify melanoma and nevus and to compare the assessment of these algorithms to that of dermatologists. […] In the experiment, the training dataset is kept up to date including 17,302 images of melanoma and nevus which is the largest dataset by far. The model performance is compared to that of 157 dermatologists from 12 university hospitals in Germany based on the same dataset. The experimental results prove that our proposed approach outperforms all 157 dermatologists and achieves higher performance than the state-of-the-art approach with area under the curve of 94.4%, sensitivity of 85.0%, and specificity of 95.0%".
The AI system in question uses object detection and classification of skin images by labeling them as cancerous or non-cancerous.
7. Systems that help detect the poaching of protected animals/species and their illegal trafficking:
The Center for Artificial Intelligence for Society at The University of South Carolina has developed an AI system called SPOT, implemented by Air Shepherd, which uses infra-red to quickly detect poachers and protected animals in areas where the protected animals are present. The system proves to be faster than ground-based methods and it does not require expert pilots on the ground, which allows the latter to focus on other risk points.
At this point, now at the end of this Artificial Intelligence 101 series, the reader should have a general sense of the current status of AI, some of its major risks along with ways to mitigate them but, most importantly, enough reasons to make them consider that AI is worth staying with us due to its potential to benefit modern societies. It is also worth providing a final general conclusion on the 101 Artificial Intelligence series:
The relationship between AI and human rights is complex and delicate, but it is here to stay and we already see its effective impact on our environment. The need to regulate the use of these systems globally and mitigate their risks is urgent.
Reducing the risk of human rights violations arising from the implementation of AI systems is key to building public confidence in the use of this technology and creating positive synergies so that these systems can help us in our daily lives. We are facing a time of change and we must be able to educate, inform and raise awareness among as much of the population as possible regarding the advantages and risks that AI poses in our lives, in order to maximize its benefits.
Establishing a universal concept of what is fair is practically impossible, so in order to achieve the most objective and fair treatment possible by AI systems, we may need to stick to each specific case and, for this, we need legal certainty, starting with the regulation of the AI systems creation process and setting the criteria of responsibility attributable to the agents involved in the whole process.
As noted in the 101 Artificial Intelligence series, the good news is that, once the risks have been identified, we can offer solutions. We may not achieve zero risk, but we need to work to get as close to it as possible.
No one who benefits from society should be interested in implementing AI systems without safeguards, whether from an ethical and professional perspective or from an economic and profit-making one. This can lead to a bad reputation for a business that does not respect fundamental rights. The resulting consequences can be devastating for a big tech or a government institution.
In the words of Nick Bostrom, Professor at Oxford University and Director of the Future of Humanity Institute:
"The biggest threat is the longer-term problem introducing something radical that’s super intelligent and failing to align it with human values and intentions. This is a big technical problem. We’d succeed at solving the capability problem before we succeed at solving the safety and alignment problem". (Marr, 2020).
The examples provided in this article are just some examples of the different sectors where AI systems are already contributing to social good. This is the main idea that should stick to the mind of the reader at the end of the day. Despite all the AI systems' risks outlined in the former articles, their benefits may very well outweigh their downsides. The adjustments still to be made are the ones that will ensure the regulation and mitigation of AI systems’ risks to the lowest possible rate so that humans and the entire world can benefit from the good impact AI systems can provide.
Chui, M. et al. (2018). Notes From the AI Frontier – Applying AI For Social Good. McKinsey Global Institute. https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artificial%20intelligence/applying%20artificial%20intelligence%20for%20social%20good/mgi-applying-ai-for-social-good-discussion-paper-dec-2018.ashx
European Union Agency for Fundamental Rights. (2018). #BigData: Discrimination in data-supported decision making. https://fra.europa.eu/sites/default/files/fra_uploads/fra-2018-focus-big-data_en.pdf.
Marr, B. (2020). Is Artificial Intelligence (AI) A Threat to Humans? Forbes. https://www.forbes.com/sites/bernardmarr/2020/03/02/is-artificial-intelligence-ai-a-threat-to-humans/
Microsoft (2022). FarmBeats. Ai, Edge & IoT to Agriculture. Microsoft. https://www.microsoft.com/en-us/research/project/farmbeats-iot-agriculture/
Pham, TC., Luong, CM., Hoang, VD. and Doucet, A. (2021). AI outperformed every dermatologist in dermoscopic melanoma diagnosis, using an optimized deep-CNN architecture with custom mini-batch logic and loss function. Nature – Scientific Reports. https://www.nature.com/articles/s41598-021-96707-8
BriteInnovationReview. [AI for good] [Screenshot] (2022). https://brite.nridigital.com/brite_summer19/ai_for_good_artificial_intelligence_in_sustainable_develop
Frontier Science News. (2017). [Fontiers in robotics and ai polani empowerment robot ethics] [Digitally designed image]. Blog. https://blog.frontiersin.org/2017/07/27/frontiers-in-robotics-and-ai-empowering-robots-for-ethical-behavior/
Macellari, E. (2018). [unknown] [Illustration]. https://www.nytimes.com/2018/03/07/opinion/artificial-intelligence-human.html
Microsoft (2022). [FarmBeats] [Photography with digital illustration]. Microsoft. https://www.microsoft.com/en-us/garage/wall-of-fame/farmbeats/
The Regulatory Review. (2021). [AI used in a surgery rooom] [Photography with digital design]. https://www.theregreview.org/2021/10/18/chung-how-will-health-care-regulators-address-artificial-intelligence/