A Better Future Through Technology: Designing AI to Benefit Humanity
The future is coming, and it’s going to be wild. And as if that isn’t enough, here comes a new set of technologies: artificial intelligence (AI). The technology — a collection of software technologies capable of learning, reasoning about the world, and making decisions for themselves — is at the entry point of our lives. Some pundits are calling it an existential threat; others are more optimistic. The bottom line is that AI will have a massive impact on this planet in the decades to come — and no one can tell you how it will play out.
But it’s not all doom and gloom. While we’re still barely scratching the surface on AI, there are some positive signs already. Algorithms are getting better at taking pictures (deep neural networks), and car companies are designing autonomous vehicles that don’t need human drivers (machine learning). Retailers like Target also use AI to predict what you’ll buy based on previous purchases (customer relationship management).
These technologies aren’t just for the big players either. There are tons of small businesses using machine learning to make their operations more efficient, from restaurants using chatbots to order food online to dry cleaners using predictive analytics to reduce wait times for customers.
In short, we’re in the midst of a revolution as big as the Industrial Revolution itself! And while there will be bumps along this road — we’re only human, after all — it’s time to embrace these new technologies with open arms and minds. But how can you ensure that developers are building AI that benefits humanity?
Defining ‘Benefits to Humanity’
First, you need to understand what constitutes “benefitting” humanity. In this context, it means creating an AI capable of learning and reasoning about the world and making decisions for itself — a technology that has been called “the most significant invention of all time.” It is a technology that will enable humans to create machines as intelligent as humans.
Second, you need to define what constitutes a benefit. In this context, ‘a benefit’ improves the quality of life for humans — whether it’s improving your health or increasing your happiness. It is not the same thing as simply making people happier; it’s about improving their lives.
It’s important to note that these concepts have been around since the 1950s when Alan Turing proposed his test to determine whether computers could think like humans. And while these terms have evolved, they still represent an important distinction between what is meant by “benefit” and what isn’t.
Start With the User and Work Backwards
The best products start with a deep understanding of user needs- It is what it means to “start with the user and work backward.”
This thought process leads to products that are incredibly simple and elegant. They work, and people love them as a result.
Taking search as an example, When Google came to be years ago, most tools for finding information were directories of links organized into categories: Yahoo, Netscape’s Open Directory, AltaVista, and so on.
Google took a fundamentally different approach. Instead of managing the web into topics (as these other sites did), the algorithms ranked pages based on their relevance for a given query. Every time you typed in a new question, Google would order the results differently depending on which pages best matched your search terms.
It was an essential shift in thinking about how best to organize information: not by hand but by having computers understand queries and determining which web pages were most relevant to those queries.
Users loved this approach because it worked better than anything else out there at the time — and it still works well today!
Embrace Transparency and Auditability
These principles are essential, but none are as crucial as transparency and the ability to take an audit. If an AI system is not explainable and transparent, people will not trust it, no matter how much value it creates.
Even if an AI system has incredible accuracy, many stakeholders will still be skeptical of its output. It is why developers must design AI systems to be transparent and interpretable by their users. Without this transparency and interpretability, users will never have trust in the system, which would inhibit adoption — even if the user gains from using the system.
Build to benefit people and society
Companies that build AI should design, test, and develop their products to comply with laws and regulations wherever they apply. As a basic principle, AI systems should not be created or operated in a way that causes unjustifiable harm.
As AI becomes part of people’s everyday lives, it is essential to encourage further research on making these systems better for humanity. For example, they should be robust against adversarial attacks (such as tricking image recognition software) and safe for use in dynamic real-world environments (such as an autonomous vehicle driving on city streets). The systems should also be secure against malicious attacks (such as spear-phishing emails targeting a specific individual).
Access to AI Should Be Inclusive and Diverse While Also Working to Prevent Bias
There are many ways to ensure that access to AI is inclusive and diverse. One of the most important ways is to understand the AI tools you are using entirely. Beyond understanding how the tool works, it is critical to know how this can harm or help different groups of people.
Another way to make AI more accessible is not to oversell its abilities. People often think that technology can solve all problems without any risk. However, as you have seen with many other technologies, there are many risks associated with these tools. If you oversell the device, people might be disappointed and may never use it at all in the future. For this technology to benefit humanity, you must be honest about what it can do and what it cannot do.
While AI holds great potential to benefit humanity, it is also important to remember that this technology will significantly impact people’s lives. It would help if you considered the ramifications of AI and its place in society.
Build-in Technical Safeguards
To help ensure that the benefits of AI systems outweigh the risks, AI developers should build technical safeguards from the start.
These could help prevent or mitigate unintended consequences, such as if a system analyzes images and starts to detect racial bias in its results.
By building safeguards into an AI system early on, developers can avoid rewriting whole codebases later, which is costly and time-consuming.
There are two types of technical safeguards: audibility measures and control mechanisms. Auditability standards enable users to understand how an algorithm makes its decisions; control mechanisms allow users to influence them.
For instance, with an image-recognition model that predicts the age of people in photos, you might want to know exactly why the model mispredicted a person’s age (perhaps because it misinterpreted wrinkles as indicating old age), so you can improve it accordingly.
Control mechanisms allow you to choose what trade-offs a system should make when making predictions (for example, if you want your model for predicting age, not to factor in wrinkles as much).
These safeguards are crucial to ensuring that AI systems benefit all of humanity and don’t cause harm by unintentionally exacerbating bias or discriminating against certain groups of people.
Avoid the Race to the Bottom
Think about the brands you trust. You trust those brands due to their excellent design, sustainable business model, and great products that make brand equity. The best way to maximize your chances of success is to avoid the race to the bottom and give your customers what they want. When companies invest in technology optimized for people’s needs, everybody wins.
AI is not a panacea, and it will not solve everybody’s problems, but it can make progress on many of them — and you must use it to do just that.
The technology should be open and explainable, both for transparency and to ensure that algorithms are free from certain types of bias.
It must deepen trust between people: As humans consider how their actions impact others more deeply, AI developers should follow suit, fostering a more profound sense of empathy as they build.
In the end, AI can be a powerful tool to help humanity, and you only need to ensure that you are using it for the right things. Contact us today to learn more about how as app developers uk we can help you build AI products that positively impact humanity.