It’s time for the Federal Communications Commission to step into the future by using artificial intelligence tools to address the continuing lack of affordable broadband to many communities—an increasingly entrenched problem of “internet inequality,” which impacts our economy and democracy and threatens the future global competitiveness of our country. By adopting more sophisticated data validation algorithms, the FCC could avoid repeating past mistakes. Such algorithms can not only automate the data validation process but also can ensure consistency and learn from previous provider submissions to improve error detection. However, a validation model is only as reliable as the historical data set used to train the model. The FCC needs to change its data collection practices, but we also need new information to check the broadband provider data we’re already collecting. For example, a model could compare reported data about certain locations with provider advertisements for those same locations. Better yet, the FCC should allow Americans to comment directly on potential map errors through an improved challenge process, injecting transparency and real-world scrutiny into an otherwise opaque process.

To fix our maps we must not only improve the granularity of our data but also ensure that data submissions are vetted and validated by the commission, without having to rely on providers or consumers to make sure we get this right. Data algorithms can help achieve this goal. With better data, we will be able to make better policy and faithfully execute the core functions of our agency—including addressing internet inequality. The need for accurate data is clear, and the technology to validate that information already exists.  We must put it to work for the American people.

As the US gets set to ban certain Chinese manufacturers from selling telecommunications equipment to US service providers, CoBank is warning that rural Americans’ access to communications services could be damaged if insufficient funding is available for rural service providers to replace prohibited equipment already installed in their networks. CoBank is a key lender to rural service providers, who are the main users in the US of wireless network equipment from Chinese vendor Huawei. CoBank estimates that the cost of replacing Huawei gear may be higher than the funding the government is expected to provide. Legislators have introduced a bill that would provide up to $700 million to help carriers remove Huawei equipment from their networks and replace it with equipment from other sources. But a CoBank analysis estimates that cost at more than $1 billion for the 30 service providers identified as using Huawei equipment.

Given that the General Data Protection Regulation (GDPR) has fallen short of expectations, policymakers in other countries have an opportunity to do better, rather than repeat Europe’s mistakes. Five lessons to learn:

1. Harmonize rules -- The US should pursue a single federal data protection law.
2. Avoid hurting internet users --  Not only were consumers inundated with online cookie notifications, new corporate privacy policies and requests to re-join email lists, but they were also cut off from some websites. 
3. Don't constrain innovation -- GDPR makes it too difficult for businesses to collect and use data, particularly by requiring organizations to specify how they will use data at the outset and minimizing what they collect.
4. Minimize compliance costs
5. Avoid regulatory overload

[Daniel Castro is the vice president of the Information Technology and Innovation Foundation (ITIF) and director of the Center for Data Innovation.]