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Tag: technology risks

  • 4 Keys to Developing Ethical AI

    4 Keys to Developing Ethical AI

    Companies continue to grapple with how to use artificial intelligence (AI) technology in a way that doesn’t compromise privacy and that takes into account other key ethical considerations. It is undeniable that AI is one of the fastest-growing categories today. But if we are unable to build tools that live up to high ethical standards, not only are we doing end users a disservice, but we are failing to deliver on the promise of this technology as a force for good.

    AI and ethics has been one of the hottest topics within the technology community for decades. However, as an industry, we are still finding it hard to put our best foot forward in terms of ensuring ethical use—let alone solving the problems these systems were meant to address. Fortunately, there is one group that could be the guiding force we need: Developers.

    From the ideation process to implementation, the developer community is by far the group with the most intimate knowledge of how AI products actually work; therefore, they can have a tremendous influence on what these tools actually do and how ethical they are—and they need to be empowered to make these calls.

    With that in mind, here are four key questions that companies and their developer teams should ask as they work to build the ethical AI solutions of the future. 

    Is This Transparent in Every Way?

    If a developer ever finds themselves saying, “I don’t know,” when asked about how a product works or how the product is ultimately going to be used, production should stop immediately. The power of automation is tremendous. But given how quickly it can morph and learn, making sure that oversight and explainability are ingrained in its functionality is imperative to ensure ethical use. If this can’t be guaranteed, developers should be empowered to flag their concerns and look for ways to remedy them before continuing production.

    As AI continues to evolve, designing and developing AI systems will likely continue to lead us into areas where no clear legal, social or policy guidelines address many of the potential uses—and misuses. So, now is the time for developers to establish a transparent and clear channel of communication where they can actively raise concerns, discuss and deliberate on ethical dilemmas with diverse stakeholders. This is crucial in reducing or eliminating any negative effects of AI. Otherwise, we will continue to see the current faux pas around AI ethics continue.

    Have we Accounted for Risk or Exceeded Regulatory Boundaries?

    Virtually any big idea has its risks. Unfortunately, when it comes to AI, these risks generally involve unethical use or unintended consequences. The ongoing debate around facial recognition and AI is a perfect example of this. While this use case is intended to improve security and may have other benefits, facial recognition software comes with significant privacy risks and fears over misuse and misapplication. Moreover, because the regulatory landscape around AI is still taking shape, companies can fall into a trap of looking to exploit these gray areas in exchange for being the first to market or gaining a competitive edge. This is why companies that are not using ethical privacy-preserving AI in facial recognition implementations, for example, are having to walk back their products.

    Simply put, acting in this manner can have terrible consequences for the ethics around an AI product. But there is good news; the fix for this mistake is relatively straightforward: Instead of just making sure that products barely comply with regulatory gray areas, make sure they exceed them. Granted, this can lead to increased go-to-market time and significant leg work. However, this is the only way to realistically “future-proof” products against potential unethical use cases.

    Is This System Adaptable?

    Even the best preparation and forethought does not guarantee that a tool will operate exactly as it was intended. This is why it is so important for developers to have the ability to plan for contingencies and build adaptability into their tools so that adjustments can be made periodically if any ethical questions arise. This can be particularly helpful when it comes to addressing bias concerns that may occur as AI products learn and expand.

    Technology is a dynamic and rapidly evolving category. And as such, developers are often working on very compressed timelines. But to get AI right, developers need time to suss out the bigger picture around their products and bake in everything possible to make sure products are set up for ethical use in the short, medium and long term. If they don’t, not only will reputational damage be done to a company, but a company’s entire product pipeline could be stunted indefinitely as products need to be pulled offline entirely.

    Are Developer Teams Actually Prepared to Build Ethically?

    Setting a concrete mission statement that is centered around ethics is a great start for any technology company. But without a more systematic approach to instilling principled behavior in developer teams, companies will struggle to drive tangible results in their pursuit of building ethical products. Additionally, given how complex ethical AI development has become—thanks to innovations in quantum computing, among other things—even the most seasoned developers will have trouble keeping up with the developments and desired standards relating to a company’s ethical AI goals.

    Therefore, beyond just laying out overarching messaging, companies need to codify their ethical intentions by building an entire infrastructure that equips developers with the ongoing training and resources they need to constantly keep ethical standards in mind. If not, confusion will almost certainly ensue, missteps will occur and ethical standards will slip as a result.

    Unfortunately, despite the promise, the AI world has fallen short of meeting the ethical frameworks we need to have in place to both solve the problems of tomorrow while also serving the public good. But this doesn’t have to be the case. By asking these few simple questions, companies can empower developers and build the ethical development infrastructure that is needed for AI to achieve its full potential.

  • Reducing Poverty in the Age of Automation

    Reducing Poverty in the Age of Automation

    In 1966, more than half of the people in the world lived in extreme poverty. I don’t mean public housing, food stamps, subsidized school lunch, free health clinic poverty. I mean the type of poverty in which there’s no electricity, no running water, no toilets and open sewers, and most children never see a doctor or the inside of a classroom. Back then, people living in extreme poverty had a daily diet of gruel; not rice and beans, mind you, but mushy, flavorless, boring gruel. Violence was rampant. Infant mortality was high and living to 65 was more the exception than the rule.

    While it’s true that there were pockets of prosperity to be found in the Third World, for most people, if you didn’t live in Australia, Japan, North America or Europe, the odds were your life was not that different from a peasant living in the Middle Ages, except that maybe you had access to a TV or radio in the village square.

    Cheap Technology Contributes to Declining Rates of Poverty

    But things changed. In 1997, the number of those living in extreme poverty dropped to 42 percent of the people in China and India. By 2017, the number dropped again, this time to an amazing 12 percent in India and .07 percent in China. Now, this doesn’t mean that everybody in India and China rode around in Toyota Camrys and spent their evenings gazing at a 52-inch high-def TV, but it does mean that just about everybody went to school, saw a doctor and had some choice in what they ate for dinner. It might not seem like a lot, but when you consider that their great grandmothers could barely read a newspaper, it’s a big deal.

    This progress didn’t happen by magic, and there’s a good argument to be made that it didn’t happen because of politics. My opinion is that it’s due in good part to the proliferation of cheap technology brought about by automation.

    The Toothbrush as an Agent of Change

    Small pieces of cheap technology can make a big difference. Take the toothbrush, for example. Not that long ago, a personal toothbrush was a luxury item for many. Today there are machines that make them automatically by the dozens, for pennies in material cost. Anybody can buy one and those who can’t many times can get one for free. Think what it must be like for a 7-year-old child in a classroom trying to learn how to read while in the throes of dental pain. There wouldn’t be a lot of learning happening.

    Studies have shown that a leading indicator of good health in the long term is the practice of good dental hygiene on a daily basis. Giving a child a toothbrush and some toothpaste early in life makes a big difference. Children who brush their teeth regularly fare better. A toothbrush might seem like a trivial consumer good, but it is actually a high-impact technology that has lifted many people out of poverty.

    Faster Credit Reporting Means Less Poverty

    Another example of a small piece of automation that’s improved the lives of billions is credit reporting. Thirty years ago it took a few days to get the credit rating of a company, and getting the credit rating of a sovereign state could take longer. Today, getting a credit report takes seconds. Automated credit reporting accelerates financing, which not only makes it easier for a consumer to get a home mortgage or car loan, but also for sovereign states such as India to get large-scale, industrial goods such as bulldozers. More bulldozers translates into more roads; more roads lead to more commerce and more commerce leads to prosperity for more people. It’s a pattern that’s difficult to ignore. Just take a look at the economic growth that accompanied the expansion of the U.S. interstate highway system in the last century. In this century, the same growth pattern is underway as China grows its One Belt, One Road (OBOR) transportation infrastructure on a global scale.

    The Cellphone: A Tool for Prosperity on a Global Scale

    Which brings us to the cellphone. The first mobile phone cost $4,000. Today, you can buy a prepaid, throwaway one with service for around $50. Given the technical infrastructures required to build the phone and networking infrastructure necessary to provide service, selling a fully functional cellphone profitably at $50 is a near miracle. And, its impact goes way beyond a simple, “What time will you be home for dinner?” conversation. There’s a big difference between living in poverty and living in poverty yet having a cellphone. A cellphone puts a person on the grid even when living in a hut in a remote village in Niger. Having a cellphone means being able to solicit paying work. It means having access to simple bank services. It means being able to get medical care in an emergency. And, a cellphone can connect users with online learning resources that can enhance the educational experience for those living in parts of the world where access to secondary education is rare. It’s no wonder the Gates Foundation is focusing on programs that use cellphone technology to address issues in poverty stricken areas.

    Not only has cheap technology reduced the cost of cellphones to nearly free, it also has reduced the cost of dental crowns through 3D printing technology and international trade through automated navigation systems for ocean-going vessels. Cheap technology also has brought about free online college courses and built-in writing assistants for email clients that have had the surprising effect of giving people better command of the written word.

    The Fall of Global Death and Destruction

    Our technological achievements allow us to grow more food, educate more people and reduce the level of violence to an all-time low. Remember, 20 million Russians were killed in World War II. That’s 5 million people a year over from the beginning of hostilities in June of 1941 until the war’s end in August of 1945. We’ve not seen slaughter in such numbers since that time. Yet, news of today’s conflicts is broadcasted on a global scale, so it can seem as though millions are dying everywhere. But the actual number of people killed in armed conflicts today comes nowhere close to the number casualties that were the result of the world wars of the last century.

    As the Numbers Go Down, the Risks Become Greater

    Things are getting better for more people and we technologists have been significant contributors to these improvements. Yet, new risks are on the horizon that could stifle the upward trends. One of the biggest potential dangers is a worldwide pandemic. While cheap air travel has removed the barriers of international travel for more people, it also has made it easier for a highly contagious disease such as Ebola to spread faster.

    And then there’s always the risk of nuclear catastrophe. The number of nuclear weapons has decreased, but technology has made possible nuclear devices that are the size of a suitcase. Whereas it takes the resources of a sophisticated sovereign state to create and deliver missiles capable of a nuclear strike across continents, all that is required for a non-state belligerent to deliver a nuclear blow is a small device hidden in the trunk of a car driven across an unguarded frontier. It’s a remote possibility but a possibility nonetheless, and one that can have a catastrophic outcome of unimaginable dimensions. Fortunately, for better and worse, we in technology have created planetary surveillance systems that make it possible to guard against such an occurrence.

    Considering the Big Picture

    Technology grows in complexity every year, particularly for those of us in DevOps. The rate of innovation can be overwhelming. We’ve got to know more to do more. As such, many of us give most of our attention to the details that make the technology work. Sometimes we lose sight of the big picture. But, here’s something to consider: As weird as it may sound given current perceptions, there’s a good argument to be made that, given the increasing rate of technological innovation and the reduced costs of mainstream technology produced by such innovation, we might eradicate extreme poverty in our lifetime, if not the lifetime of our children. In the past such thinking was considered grandiose. But, as the $50 cellphone demonstrates, it’s a goal we can look forward to achieving.

    Authors note: The source of the data on the reduced rates of poverty worldwide described in the opening of this article comes from the book, “Factfulness” (pages 52-53) by Hans Rosling , Anna Rosling Rönnlund and Ola Rosling.

    — Bob Reselman