In June 2015 Google Photos’ facial recognition software labeled a picture of a black computer developer as a “gorilla.” The problem was so difficult to solve that as of January 2018 Google was simply not identifying anything as a gorilla, chimpanzee or monkey, according to a Wired report. The following year the American Civil Liberties Union and 16 other institutions protested data being used to create “predictive policing” algorithms designed to forecast where crime might occur, describing the data as “profoundly limited and biased,” resulting not in less crime but in further concentration of policing in already heavily policed neighborhoods. Then, just last year, Amazon reportedly shuttered a years-long project designed to let an artificial intelligence algorithm sort through hundreds of résumés to aid in hiring when it was discovered the data that had been used to teach the algorithm was biased against women. The reasons algorithms behind AI become biased are myriad. But one of the most common explanations is that the data used to teach the algorithms are themselves biased—“garbage in, garbage out.” With data coming from a wide range of constantly changing sources, the “lessons” the algorithms learn can be difficult to reverse-engineer, making it nearly impossible to understand why an artificial intelligence became biased. One possible solution, according to Adam Caplan, Salesforce’s head of blockchain, is to structure and track the disorganized data using a shared, distributed ledger, or blockchain, similar to the ledger that tracks bitcoin transactions. At the fifth annual Blockchain Summit, Caplan described how the consumer resource management (CRM) giant is looking into ways blockchain can track the origin of biased data. The summit, which aims to inspire interdisciplinary projects that benefit society, is hosted by Bitfury, a member of Forbes Blockchain 50. “Blockchain can be really powerful in terms of how these algorithms are made and what’s influencing them,” said Caplan, who led the launch of Salesforce Blockchain last month. “Or if there is bias in AI to be able to understand how that came about.” If the new project is successful, Salesforce believes there could be more than $1 trillion in revenue to be unlocked from artificial intelligence. Salesforce’s research into using blockchain to track the data is being managed by the company’s artificial intelligence team, Caplan said. While Salesforce is currently sharing very little about the project, Caplan says the research could eventually be used to identify the source of biased data in a wide variety of algorithms, including those that increasingly power chat bots and AI avatars like virtual celebrity Lil Michaela, who has 1.6 million followers on Instagram. With the rise of even more advanced personal assistants like Amazon's Alexa and Apple's Siri, a 2017 report commissioned by Salesforce predicts that $1.1 trillion dollars in new revenue and 800,000 new jobs will be generated by 2021. Salesforce customers alone could account for $293 billion of that revenue and 155,000 employees over the same period of time. That is, assuming the algorithms don’t start misbehaving. While Caplan believes most bias in algorithms is unintentional, he says Salesforce is being proactive by searching for ways its clients can conduct deep dives into data from diverse data sets before it becomes a problem. “Certainly we’re thinking about diversity, inclusion and bias and how we can make sure we’re enabling enterprise companies to do the right thing and are transparent,” Caplan says. To give an idea of which enterprises might be among the first to benefit from the research, last month Caplan launched Salesforce Blockchain, a project using Hyperledger Sawtooth to make it easier for enterprises and educational institutions to form groups that can save money or time by using a shared distributed ledger to cut out unnecessary middlemen. At its launch, Salesforce announced that four clients are already using the blockchain platform, including financial information giant S&P Global and Arizona State University. Most algorithms are developed internally and can therefore be tracked using existing, centralized code repositories like GitHub that let developers view one another’s code before confirming bug fixes and modifications. But in the future, AI could be asked to make decisions based on data locked behind the closed doors of competing organizations less likely to share data, according to another Blockchain Summit panelist, David Treat, co-lead of Accenture’s blockchain business. Speaking on the same panel, Treat said companies writing algorithms to answer complicated questions have historically been reluctant to share data with competitors—regardless of their own possible gain—for fear they might accidentally help out the competition. But this undercuts another possible way to remove bias from algorithms: More data, from the most diverse possible sources, has a tendency to cancel out biased lessons algorithms accidentally learn. To that end, Accenture is also exploring blockchain. The consulting firm that specializes in blockchain is developing a modified version of what is called homomorphic encryption, which lets data scientists operate on encrypted data without decrypting the data itself. Called shared homographic encryption (SHE), the technology is being customized by Accenture for companies cooperating on a shared blockchain accounting system, or another similar distributed ledger. Algorithms could learn from data provided by competing companies, without ever needing to know what the data is, and pinpoint exactly when the bias was introduced. “If I wanted to develop an actual AI algorithm that’s going to give us a great answer I want to be able to draw from cross-organizational data sets,” Treat says. “And knowing, what you pulled from where, how was it used, is critically important when you’re looking at fairness and responsible use.” Stay informed and ahead of the crowd with Forbes Crypto Confidential, a free weekly e-letter. Sign up today.
San Francisco firm Salesforce has said there are $1tn in revenues to be made from AI-backed algorithms, and blockchain could provide the solution to the issue of bias in AI. CaplanAdam Caplan, Salesforce's head of blockchain, said it could be used to find the origin of bias in data, as well as understand how it occurred. Adam Caplan added blockchain could also facilitate the use of cross-organisational data via shared homographic encryption, reducing bias by increasing the diversity of possible sources.