AI is a powerful tool with many potential applications in social or environmental change. But, while it is certainly not perfect, it can be a powerful tool for NGOs, especially those that are struggling to meet their financial or staffing needs. To achieve social good using AI, NGOs need guidelines to help them make the most of it. Below are the guidelines. Here are four important points for NGOs to consider:
Ethics
Although AI for social purpose projects tend to be glorified as a way to alleviate societal problems and empower people, these projects often fail to take into account human rights and the rights for people from disadvantaged populations. Some definitions of AI for social good describe initiatives aimed at solving unsolved societal problems, while others refer to projects that benefit a particular group without consideration for the economic implications of those solutions. These AI projects can often be harmful to people from disadvantaged communities and raises important ethical questions about how they should be viewed.
Transparency
Transparency is crucial for many different issues. Unclarity in the AI system's goals can cause confusion, and even harm. For example, an AI system designed to remind users of their medication may seem intrusive. This could make it more vulnerable. But such systems don't appear like human beings and aren't meant to force people into certain actions. AI systems can be disabled by patients.
Diversity
AI4SG projects have to encourage inclusion and diversity. AI applications that work well will include all. Google's AI for Social Good program aims to accomplish this. Click here to learn more about the program. The Oxford Initiative on AIxSDGs, a database that focuses on AI projects that are aiming to achieve SDGs, is curated by Oxford. It indexes more than 100 projects and is expected to support formal research in this field. Other attempts at a repository are the ITU AI Repository and the AI Commons knowledge hub. Each of these have 71 members who support 21 AI4SG programs. Meta-initiatives such as these can connect organisations and combine knowledge from different AI4SG project.
Trustworthiness
Recently, concerns about the trustworthiness of AI have gained much prominence in public policy discussions. The European Commission High-Level Expert Group on Artificial Intelligence HLEG AI released its Ethics Guidelines to Trustworthy AI. They have already received a lot of traction from both research and practice. Other such guidelines, including the Principles of Socially Beneficial AI published by the White House and OECD, share the same goals.
Collaboration
The trend of using artificial intelligence (AI) to benefit society has grown in recent years. But, how do we put it to use? AI for social benefit explores how AI can be used to solve society's problems. This course will introduce you to the many AI techniques that can help with a wide range of social issues. The course also discusses how AI can aid in fighting blight and improve policing.
Prices
Consider the SDGs as a lens to assess the social benefits of AI. These goals are interrelated, and achieving them requires a collective effort. AI applications may benefit one SDG but harm another. AI for social benefit should recognize the interconnectedness between these goals. AI applications should maximize the positive impact on all SDGs and minimize their negative effects.
FAQ
Who invented AI?
Alan Turing
Turing was conceived in 1912. His father, a clergyman, was his mother, a nurse. At school, he excelled at mathematics but became depressed after being rejected by Cambridge University. He started playing chess and won numerous tournaments. He worked as a codebreaker in Britain's Bletchley Park, where he cracked German codes.
1954 was his death.
John McCarthy
McCarthy was born 1928. He studied maths at Princeton University before joining MIT. There he developed the LISP programming language. He was credited with creating the foundations for modern AI in 1957.
He died in 2011.
What is the future role of AI?
Artificial intelligence (AI), the future of artificial Intelligence (AI), is not about building smarter machines than we are, but rather creating systems that learn from our experiences and improve over time.
So, in other words, we must build machines that learn how learn.
This would involve the creation of algorithms that could be taught to each other by using examples.
Also, we should consider designing our own learning algorithms.
It's important that they can be flexible enough for any situation.
How does AI work
It is important to have a basic understanding of computing principles before you can understand how AI works.
Computers keep information in memory. Computers use code to process information. The code tells computers what to do next.
An algorithm refers to a set of instructions that tells a computer how it should perform a certain task. These algorithms are typically written in code.
An algorithm can be considered a recipe. A recipe could contain ingredients and steps. Each step can be considered a separate instruction. One instruction may say "Add water to the pot", while another might say "Heat the pot until it boils."
How does AI work?
An algorithm is an instruction set that tells a computer how solves a problem. An algorithm can be described in a series of steps. Each step has a condition that dictates when it should be executed. A computer executes each instruction sequentially until all conditions are met. This is repeated until the final result can be achieved.
For example, suppose you want the square root for 5. If you wanted to find the square root of 5, you could write down every number from 1 through 10. Then calculate the square root and take the average. However, this isn't practical. You can write the following formula instead:
sqrt(x) x^0.5
This will tell you to square the input then divide it twice and multiply it by 2.
Computers follow the same principles. The computer takes your input and squares it. Next, it multiplies it by 2, multiplies it by 0.5, adds 1, subtracts 1 and finally outputs the answer.
Is there any other technology that can compete with AI?
Yes, but still not. Many technologies exist to solve specific problems. However, none of them match AI's speed and accuracy.
What are some examples AI applications?
AI is being used in many different areas, such as finance, healthcare management, manufacturing and transportation. Here are a few examples.
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Finance - AI already helps banks detect fraud. AI can detect suspicious activity in millions of transactions each day by scanning them.
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Healthcare - AI can be used to spot cancerous cells and diagnose diseases.
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Manufacturing - AI can be used in factories to increase efficiency and lower costs.
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Transportation - Self-driving vehicles have been successfully tested in California. They are currently being tested all over the world.
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Energy - AI is being used by utilities to monitor power usage patterns.
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Education - AI is being used in education. Students can communicate with robots through their smartphones, for instance.
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Government - AI is being used within governments to help track terrorists, criminals, and missing people.
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Law Enforcement – AI is being used in police investigations. Investigators have the ability to search thousands of hours of CCTV footage in databases.
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Defense - AI can both be used offensively and defensively. An AI system can be used to hack into enemy systems. Protect military bases from cyber attacks with AI.
Statistics
- More than 70 percent of users claim they book trips on their phones, review travel tips, and research local landmarks and restaurants. (builtin.com)
- The company's AI team trained an image recognition model to 85 percent accuracy using billions of public Instagram photos tagged with hashtags. (builtin.com)
- Additionally, keeping in mind the current crisis, the AI is designed in a manner where it reduces the carbon footprint by 20-40%. (analyticsinsight.net)
- A 2021 Pew Research survey revealed that 37 percent of respondents who are more concerned than excited about AI had concerns including job loss, privacy, and AI's potential to “surpass human skills.” (builtin.com)
- That's as many of us that have been in that AI space would say, it's about 70 or 80 percent of the work. (finra.org)
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How To
How do I start using AI?
You can use artificial intelligence by creating algorithms that learn from past mistakes. This allows you to learn from your mistakes and improve your future decisions.
To illustrate, the system could suggest words to complete sentences when you send a message. It could learn from previous messages and suggest phrases similar to yours for you.
It would be necessary to train the system before it can write anything.
Chatbots can also be created for answering your questions. If you ask the bot, "What hour does my flight depart?" The bot will reply that "the next one leaves around 8 am."
If you want to know how to get started with machine learning, take a look at our guide.