A rapid rise in digital solutions and data generation has turned artificial intelligence (AI) and blockchain into potent technologies. These technologies offer significant benefits to various industries, including finance, healthcare, customer service, and more.
AI technology thrives on data. The more data is provided to its learning algorithms, smarter and more intelligent it becomes. The technology is already playing an essential role in optimizing business processes and underpinning decision-making. Global consulting firm PwC believes that AI can transform the productivity and GDP potential of the global economy. As per their report, “AI can increase global GDP by an additional $15.7 trillion by 2030.”
Yet, the innovative technology faces multiple hindrances — particularly in bringing trust of the users in its models, analytics, and outcomes.
The AI trust deficit
Let us understand with a few examples:
You have joined an AI-based financial platform that suggests various offers and deals on credit cards, loans, and deposits from multiple banks. The platform uses advanced algorithms and vast market data to offer personalized suggestions to best suit your financial requirements. You notice that the suggestions you receive from the platform mostly include offerings from the big bank ‘X’. You also see their ad on the platform every now and then. Now you become skeptical and start thinking whether the results are biased.
You picked a doctor for your routine checkup. Your doctor has a smart AI assistant that is trained to analyze various patterns and behavior to diagnose the problem and suggest the best medication. The AI assistant is also ingested with millions of medical periodicals that might not be possible for a human. After the checkup, with advice from the AI assistant, your doctor prescribed you a couple of medicines from a big pharma company ‘Y’. The AI assistant also noted high cholesterol through your reports over the past year and advised tablets from the same company to curb it. Now you wonder who provided the training data to the AI assistant. Could it be the same big pharma company ‘Y’?
In both cases, the AI-based bot provided suggestions and advice based on the training and data it has got. How can you trust their recommendations without confirming the provenance and integrity of the data?
Combining blockchain and AI technology
Blockchain is a technology that allows real-time data transfer while ensuring better safety, security, and transparency. Blockchain can provide you with better control of your data and enhance the traceability of the data that is fed to AI algorithms. Moreover, the data can be stored on various nodes without needing a centralized database which is prone to hacks and natural disasters. See how blockchain can bring trust and confidence in AI-based processes, models, and analytics.
Better control of your data
Most tech giants, including Google, Apple, Facebook, Alibaba, and more use AI technology to offer their services. Businesses using AI face challenges to establish trust among their users. These businesses must assure that the user data is safe and being used with due permissions.
Blockchain can provide better control to users when it comes to allowing who can have access to their data. With blockchain, users can keep their data secure and accessible to only the required authorities gaining better control over their data and services they get.
Ensure data integrity
The goal of feeding data to AI algorithms is to create an accurate model that offers correct answers and appropriate recommendations every time. Blockchain can ensure better transparency to the source of data that is provided to the model. With blockchain, you can also track the origin of the training data and see an audit trail of the data being injected. It can be a key to bring trust to the outcomes and decisions derived from AI.
Enhanced data security
Cyberattacks have remained a serious threat to the data-driven world, and AI can be dangerous in the hands of hackers. Blockchain offers decentralized storage system where there is no single point of failure. There would be no need for a central database to store data which can be hacked by cybercriminals. Moreover, once the data is stored on blockchain, it can’t be altered. It can help businesses to enhance security and infuse trust amongst their users.
Businesses already doing it: Microsoft and KPMG
Mircosoft and KPMG are already exploring blockchain technology to help businesses and their clients to trust AI.
Microsoft is pitching blockchain as a way to make AI less scary for its clients. They believe that blockchain can add trust and a degree of transparency, reducing the concerns their clients generally facing when trusting AI. They released a new tool called Azure Blockchain Data Manager that takes data stored on blockchain and connect it to other applications.
Marc Mercuri, Program Manager for blockchain engineering for Microsoft Azure, said, “From manufacturing to energy to public sector to retail, AI is digitally transforming businesses in every vertical. Blockchain can ensure that everything from the algorithms to the data going in and out of them is trustworthy.”
KPMG has recently obtained a patent in the US for a blockchain-based system that aims to improve selection, curation and management of data used to train AI and ML models. The system shows how blockchain can store, track and trace data used throughout the AI lifecycle.
Marisa Boston, Director at KPMG, said, “Using blockchain allows both KPMG and our clients to confidently stand behind the responsible use of data entrusted to us.”
Integration between two game-changing technologies is not something that can happen overnight. Blockchain adoption to bring trust in AI will need time. It will depend on the evolving businesses environment as well as technical hurdles and limitations that both technologies come with. While the convergence of blockchain and AI may not solve all the problems, it may offer a better potential to restore trust in the technology.
This article has been published from a wire agency feed without modifications to the text. Only the headline has been changed.