Following reports of genocide in Myanmar, Facebook banned the country’s top general and other military leaders who were using the platform to foment hate. The company also bans Hezbollah from its platform because of its status as a US-designated foreign terror organization, despite the fact that the party holds seats in Lebanon’s parliament. And it bans leaders in countries under US sanctions.
At the same time, both Facebook and Twitter have stuck to the tenet that content posted by elected officials deserves more protection than material from ordinary individuals, thus giving politicians’ speech more power than that of the people. This position is at odds with plenty of evidence that hateful speech from public figures has a greater impact than similar speech from ordinary users.
Clearly, though, these policies aren’t applied evenly around the world. After all, Trump is far from the only world leader using these platforms to foment unrest. One need only look to the BJP, the party of India’s Prime Minister Narendra Modi, for more examples.
Though there are certainly short-term benefits—and plenty of satisfaction—to be had from banning Trump, the decision (and those that came before it) raise more foundational questions about speech. Who should have the right to decide what we can and can’t say? What does it mean when a corporation can censor a government official?
Facebook’s policy staff, and Mark Zuckerberg in particular, have for years shown themselves to be poor judges of what is or isn’t appropriate expression. From the platform’s ban on breasts to its tendency to suspend users for speaking back against hate speech, or its total failure to remove calls for violence in Myanmar, India, and elsewhere, there’s simply no reason to trust Zuckerberg and other tech leaders to get these big decisions right.
Repealing 230 isn’t the answer
To remedy these concerns, some are calling for more regulation. In recent months, demands have abounded from both sides of the aisle to repeal or amend Section 230—the law that protects companies from liability for the decisions they make about the content they host—despite some serious misrepresentations from politicians who should know better about how the law actually works.
The thing is, repealing Section 230 would probably not have forced Facebook or Twitter to remove Trump’s tweets, nor would it prevent companies from removing content they find disagreeable, whether that content is pornography or the unhinged rantings of Trump. It is companies’ First Amendment rights that enable them to curate their platforms as they see fit.
Instead, repealing Section 230 would hinder competitors to Facebook and the other tech giants, and place a greater risk of liability on platforms for what they choose to host. For instance, without Section 230, Facebook’s lawyers could decide that hosting anti-fascist content is too risky in light of the Trump administration’s attacks on antifa.
This is not a far-fetched scenario: Platforms already restrict most content that could be even loosely connected to foreign terrorist organizations, for fear that material-support statutes could make them liable. Evidence of war crimes in Syria and vital counter-speech against terrorist organizations abroad have been removed as a result. Similarly, platforms have come under fire for blocking any content seemingly connected to countries under US sanctions. In one particularly absurd example, Etsy banned a handmade doll, made in America, because the listing contained the word “Persian.”
It’s not difficult to see how ratcheting up platform liability could cause even more vital speech to be removed by corporations whose sole interest is not in “connecting the world” but in profiting from it.
Platforms needn’t be neutral, but they must play fair
Despite what Senator Ted Cruz keeps repeating, there is nothing requiring these platforms to be neutral, nor should there be. If Facebook wants to boot Trump—or photos of breastfeeding mothers—that’s the company’s prerogative. The problem is not that Facebook has the right to do so, but that—owing to its acquisitions and unhindered growth—its users have virtually nowhere else to go and are stuck dealing with increasingly problematic rules and automated content moderation.
The answer is not repealing Section 230 (which again, would hinder competition) but in creating the conditions for more competition. This is where the Biden administration should focus its attention in the coming months. And those efforts must include reaching out to content moderation experts from advocacy and academia to understand the range of problems faced by users worldwide, rather than simply focusing on the debate inside the US.
Banks need to strike the right balance for digital transformation
Every financial institution is looking to digital transformation to meet rising customer expectations for speed and convenience, lower its operating cost, and fend off competition, including from tech companies moving into financial services. Some are spending over 10% of yearly revenue on technology investments, according to Bloomberg. “This is a huge investment and most financial institutions cannot support this for the long term,” says Michael Fei, SME banking CEO at OneConnect Financial Technology, an associate of Ping An Insurance.
The covid-19 pandemic has revealed how even financial institutions that considered themselves digitally advanced are, in reality, still wedded to analog processes along the chain of processing.
“For many financial institutions, this has been a wake-up call,” says Fei. “In the past, many had thought that if they have an online portal and a mobile application then that’s enough. But now they’ve realized it’s not. Some banks have online portals and mobile apps where you can apply for loans, but they still need to send items to the customer and carry out on-site inspection before they can process the loans, which hasn’t been possible during covid. Banks have had to reshape and redesign the whole process of their lending products.”
Banks have also realized their lack of truly deep customer knowledge, which is crucial to inform responsible and flexible decisions during an economic downturn as customer needs rapidly change.
“Now that everything is digital, financial institutions are realizing how little they knew their customers,” says Tan Bin Ru, chief executive officer for Southeast Asia at OneConnect Financial Technology. “Customer hyper-personalization tools, to understand what products to offer, have been acknowledged conceptually for a long time but not implemented—now banks are moving towards it and really getting tools to do it.” Traditional banks that were not previously utilizing alternative datasets now want to integrate them more into secure lending, Tan says.
The power of partnerships
Banks have increasingly understood they need outside help to execute their digital transformation agenda. “Banks usually have very rigid systems and procedures,” says Fei. “For instance, if you want to launch a new product you have to follow the process, and it takes at least six months. In the age of digitalization, this doesn’t work, as customers want things immediately. This has put huge pressure on these financial institutions to build agile operations and systems to be able to respond to the needs of their customers.”
But the number of tech companies pushing into financial services can be overwhelming and not all of them have domain expertise, which can lead to misguided attempts to apply new technologies everywhere. Without experience of financial services, tech companies may also underestimate the trade-offs involved in deploying certain digital tools.
OneConnect combines expertise in digital technology with deep knowledge of banking. Fei, who has past experience working at HSBC China and Bank of Langfang, a Chinese commercial bank, describes one partnership with a Chinese national bank to reimagine its customer service center as an illustration of why banking experience matters in digital reform. The lender was looking to transform a 6,000-person call center toward a more intelligent, AI-enabled approach with greater use of automation. But automating customer services must be done carefully; customers will not appreciate being handed off to a robot for certain sensitive or urgent inquiries where a human counterpart is desired.
OneConnect built a knowledge map with the bank, to understand and anticipate what problem a customer is trying to solve with a given query, and then understanding when and where to apply automation versus human support. “This required extensive understanding of the business and the industry, which many technology companies do not have,” he says. “You need that, to know when to intervene, what should be done by robotics and what should be a human being. Many tech companies cannot offer this.”
Rather than advocating digital transformation across the board, OneConnect works to get the right balance between customization and integration, and to appreciate that banks are looking for a blend, or omnichannel approach. “Our banking customers, and their customers, want to be offline for certain things, and online for others; they want that flexibility,” says Tan.
A second partnership problem banks face is the sheer number of technology vendors and startups, which can be overwhelming and complicate their digital transformation journey. It is unclear which fintechs will survive and which will not; startups might offer an appealing technology, but if their underlying business model proves unviable, or they cannot raise sufficient funding to support their expansion, or they pivot to a new direction, a bank is exposed.
In many cases, banks take on many different fintechs because no single startup can manage the breadth of their needs, or because the bank wants to diversify its risk. “Since the digital journey is such a long process, a lot of banks feel they need to look at 15 to 20 fintechs to piece together their journey, but the more players they have, the more risk there is,” says Tan.
OneConnect solves both problems—an overly complicated vendor network and the risk of working with fledgling tech companies—by offering a broad sweep of turnkey solutions, with the commercial scale and security that customers can rely on. Typically, a bank will chart its desired journey and up to 80% of those solutions can be provided by OneConnect, says Tan. The company, publicly traded on the New York Stock Exchange, also draws on over 30 years of experience in financial services of its parent company, Ping An, described by The Economist as a window into the future of finance. “No other traditional financial-services group in the world comes close to rivaling Ping An’s ability to develop technologies and deploy them at such a scale,” the magazine recently wrote.
OneConnect: The journey so far
OneConnect has built a broad business in China, serving all of its major banks, 99% of its city commercial banks, and 53% of insurance companies. But its footprint is increasingly global, with over 50 international customers in more than 15 markets, including Singapore, Indonesia, Malaysia, Philippines, and Abu Dhabi.
The company has built new technology solutions to enhance pricing accuracy, such as an alternative data, AI-based credit scoring model for a credit bureau in Indonesia, and supported Malaysian banks to develop user-friendly apps, digital portals, and onboarding. It is leveraging image recognition, a core enabler of “insur-tech” that allows insurers to quickly assess damage claims and pay out to eligible beneficiaries. OneConnect has partnered with Swiss Re, a European insurer, to develop a digital end-to-end solution for motor claims handling, based on AI-based image recognition and advanced data analytics. The tool can analyze photos of vehicle damage, identify repair needs and costs within minutes, offer cash payments, and even offer value-added services, like directing drivers to a repair garage.
OneConnect is also helping build the fintech ecosystem by working with governments, regulators, and stakeholders. It is working with Singapore’s blockchain association to build the skills, literacy, and talent pool needed to enable innovation and has partnered with Abu Dhabi Global Market, a financial center in the United Arab Emirates, to support the development of a “digital lab,” a sandbox for fintechs to collaborate and develop their innovations.
Working closely with its partners at home and abroad, OneConnect is helping the finance industry move swiftly into the digital era by leveraging the right tools at the right time, benefiting customers and finance institutions alike by widening access to services and lowering costs.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.
Will your neighbors get vaccinated?
As the coronavirus vaccines have rolled out across the US, the process has been confusing and disastrous. States, left by the federal government to fend for themselves, have struggled to get a handle on the logistics of distribution. Many, including Georgia, Virginia, and California, have fallen woefully behind schedule.
But even if there were a perfect supply chain, there’s another obstacle: Not all Americans want the vaccine.
Survey data gathered through Facebook by Carnegie Mellon University’s Delphi Lab, one of the nation’s best flu-forecasting teams, showed that more than a quarter of the country’s population would not get vaccinated if it were available to them today. How people feel about receiving vaccinations varies widely by state and county. The percentage of respondents who would accept a vaccine falls as low as 48% in Terrebonne parish, Louisiana, and peaks as high as 92% in Arlington county, Virginia.
The findings are extremely worrying. The fewer people who are vaccinated, the longer the virus will continue to ravage the country, and prevent us from returning to normal. “It’s one of those things that probably shouldn’t have surprised me,” says Alex Reinhart, an assistant teaching professor in statistics & data science, who was part of the research. “But when you look at the map, it’s still surprising to see.”
The good news—and there is some good news—is that this data could also help fight public hesitancy. The Delphi Lab has been helping the CDC to track and understand the spread of covid infections since the beginning of the pandemic. The latest survey will help the agency identify where to perform more targeted education campaigns. The research group is also working with several county-level health departments to inform local outreach.
The Delphi researchers collected the data via a large-scale survey that it has been operating through Facebook since April 2019. It works with the social media giant to reach as wide a cross-section of the US population as possible, and surfaces daily questions to a statistically representative sample of Facebook users. An average of 56,000 people participate daily, and the company itself never sees the results.
During the pandemic, the survey has included a variety of questions to understand people’s covid-related behaviors, including mask adherence, social distancing, and their mental health. Some of the results are fed into the lab’s coronavirus forecasting model, while others are summarized and given directly to public health officials and other academic researchers. The questions are regularly updated, and the vaccine acceptance question was added at the start of January—after the first vaccines had been authorized by the US government.
The map visualizes each county’s polling average from January 1 to January 14. For counties with too few daily respondents—less than 100—the Delphi researchers grouped the data from neighboring counties. This is reflected in our map above, which is why various clusters of counties show up with the same percentage. The researchers also independently verified their results with some of the CDC’s own surveys and Pew Research.
Next, the researchers plan to expand their survey to understand why people are reticent about the vaccine. They’re also exploring questions that could help identify what blocks people from accessing vaccines, especially for at-risk populations.
This story is part of the Pandemic Technology Project, supported by the Rockefeller Foundation.
Worried about your firm’s AI ethics? These startups are here to help.
Parity is among a growing crop of startups promising organizations ways to develop, monitor, and fix their AI models. They offer a range of products and services from bias-mitigation tools to explainability platforms. Initially most of their clients came from heavily regulated industries like finance and health care. But increased research and media attention on issues of bias, privacy, and transparency have shifted the focus of the conversation. New clients are often simply worried about being responsible, while others want to “future proof” themselves in anticipation of regulation.
“So many companies are really facing this for the first time,” Chowdhury says. “Almost all of them are actually asking for some help.”
From risk to impact
When working with new clients, Chowdhury avoids using the term “responsibility.” The word is too squishy and ill-defined; it leaves too much room for miscommunication. She instead begins with more familiar corporate lingo: the idea of risk. Many companies have risk and compliance arms, and established processes for risk mitigation.
AI risk mitigation is no different. A company should start by considering the different things it worries about. These can include legal risk, the possibility of breaking the law; organizational risk, the possibility of losing employees; or reputational risk, the possibility of suffering a PR disaster. From there, it can work backwards to decide how to audit its AI systems. A finance company, operating under the fair lending laws in the US, would want to check its lending models for bias to mitigate legal risk. A telehealth company, whose systems train on sensitive medical data, might perform privacy audits to mitigate reputational risk.
Parity helps to organize this process. The platform first asks a company to build an internal impact assessment—in essence, a set of open-ended survey questions about how its business and AI systems operate. It can choose to write custom questions or select them from Parity’s library, which has more than 1,000 prompts adapted from AI ethics guidelines and relevant legislation from around the world. Once the assessment is built, employees across the company are encouraged to fill it out based on their job function and knowledge. The platform then runs their free-text responses through a natural-language processing model and translates them with an eye toward the company’s key areas of risk. Parity, in other words, serves as the new go-between in getting data scientists and lawyers on the same page.
Next, the platform recommends a corresponding set of risk mitigation actions. These could include creating a dashboard to continuously monitor a model’s accuracy, or implementing new documentation procedures to track how a model was trained and fine-tuned at each stage of its development. It also offers a collection of open-source frameworks and tools that might help, like IBM’s AI Fairness 360 for bias monitoring or Google’s Model Cards for documentation.
Chowdhury hopes that if companies can reduce the time it takes to audit their models, they will become more disciplined about doing it regularly and often. Over time, she hopes, this could also open them to thinking beyond risk mitigation. “My sneaky goal is actually to get more companies thinking about impact and not just risk,” she says. “Risk is the language people understand today, and it’s a very valuable language, but risk is often reactive and responsive. Impact is more proactive, and that’s actually the better way to frame what it is that we should be doing.”
A responsibility ecosystem
While Parity focuses on risk management, another startup, Fiddler, focuses on explainability. CEO Krishna Gade began thinking about the need for more transparency in how AI models make decisions while serving as the engineering manager of Facebook’s News Feed team. After the 2016 presidential election, the company made a big internal push to better understand how its algorithms were ranking content. Gade’s team developed an internal tool that later became the basis of the “Why am I seeing this?” feature.