Data privacy, distracting smartphones and unethical AI: How mobile technology is part of the problem and the solution
Consumers were full of concerns about data privacy in 2017, smartphones are distracting us more than ever, and the danger of using artificial intelligence (AI) unethically is growing. Is mobile technology part of the problem? If users are not confident that their data is protected, if apps distract us instead of making us more productive, or if AI isn’t used in ways that help people, consumers will stop using the technology we create.
Making mobile technology part of the data privacy solution
The good news is that technologies and practices are emerging to address these issues, which users will increasingly see in the products that are offered. Here are a few important developments to begin expecting:
1. User-controlled data: When it comes to data privacy, 61 percent of consumers said they are reluctant to hand large companies more data than they currently hold. It was also found that two-thirds of consumers said they are concerned how brands use their personal data. We need unambiguous policies on how user data is being used, simple ways of expressing this usage that everyone can understand, and technology to enforce it. Some apps already do this, but they are the exception to the rule. There needs to be a ubiquitous, simple and standard way for a user to express how his data can be used. Anyone should be able to say that they do not want their data used, or that they only want data used for a specific reason. Enforcement needs to be built into the core architecture of the devices. This is the only way we will restore user confidence that they truly own and control their personal data.
— IBM Mobile (@ibmmobile) February 20, 2018
2. Focused applications: The detrimental effects of smartphones on concentration and productivity is always a hot topic. Recently, The Guardian documented the growing addictive and manipulative techniques of social networks. Applications bombard us with irrelevant information and options. Too often, they promote what they want us to do. The era of generic, one-size-fits-all apps is over and will give way to apps customized to the user’s current situation and context — human-like assistants that help us to accomplish our goals. These apps will often anticipate our needs and provide useful suggestions. When going to a hospital for some tests, for example, an app should remind us in advance of what preparations we need to perform based upon our medical condition and the tests being conducted. When we arrive, the app should optimize our visit, directing us to the labs and areas with the shortest waiting times. It can suggest the closest cafeteria or rest area during long waits. Apps should help remove drudgery from our lives and make it easier to attend to unpleasant situations, such as hospital visits.
3. Augmented reality (A/R): A/R technology is a great example of the trend just mentioned, where the app can become a true assistant. While we often think of A/R in terms of games, it will increasingly provide productivity enhancements to employees and assistance to individuals. For instance, we already use A/R to help consumers understand features in appliances by superimposing information about the features on top of app’s camera view. It can walk a consumer, step by step, through diagnostic procedures, or make suggestions of what worked in other, similar situations. It can help a maintenance worker locate a building’s A/C unit, thereby increasing efficiency and reducing repair time.
4. AI-at-the-edge: It may seem that these trends are in conflict. Can we have more focused and intelligent apps while we protect data privacy at the same time? If intelligence relies on collecting information, how do we reconcile that with privacy concerns? The concerns over the ethics of artificial intelligence are growing as more questions arise as AI technology advances and becomes more mainstream. One solution lies in “AI-at-the-edge.” Today, most AI requires sending all the data to the cloud for analysis. But as devices continue to increase in computational capability, we can have the best of both worlds. Data that needs to be kept private is processed on the device and stored there, encrypted. Only data that does not compromise privacy is sent and processed in the cloud. One example of using data-at-the-edge combined with cloud computing can be found in The Guardian, which reported on pay-as-you-go car insurance; in this plan, the driver pays only for his actual driving usage. To alleviate privacy concerns, some companies send only summary mileage reports, relying on the device for computation. As AI-at-the-edge computing models become better understood, the device’s level of sophistication will increase, relaying only limited or anonymous information to the cloud.
Technology is being developed at a faster pace than ever. We should not be afraid of it, but use it wisely to improve lives and unleash creativity while protecting data privacy. If we do this diligently, apps will then no longer be part of the problem, but part of the solution.