AI is a new generation technology where machines and information systems demonstrate a form of intelligence that simulates the natural intelligence of human beings in interacting with the environment. However, the success of any AI-based system also depends on the trust displayed by the beneficiaries on AI technology, besides other factors. Data, models, and analytics are the three key components of AI technology. One can decentralize these three key components using blockchain technology, and it will undoubtedly enhance the end users’ trust and confidence levels in AI-based systems.
Understanding key characteristics of blockchain technology
Seemingly, blockchain technology promises to solve many problems. However, a lot has yet to be explored as the global blockchain adoption will increase significantly in time to come. As per a Statista forecast, the global blockchain technology revenues are expected to soar to more than $39 billion by 2025.
The key characteristics of blockchain technology that make it so popular and appealing are:
- Decentralized technology: There is no central authority to monitor the network, unlike the traditional banking system. Authentication and authorization of transactions can take place without the help of any single ruling power.
- Distributed ledgers: Instead of storing data in a central repository, it is synchronized, shared, and recorded in various nodes in a shared infrastructure.
- Consensus-based: Any transaction in the blockchain network is executed when all pertinent network nodes agree on the transaction.
- Immutability & security: In the Blockchain network, a transaction, once recorded, cannot be altered by anyone at any time. Hashing is irreversible in the case of Blockchain, which makes the technology highly secure.
Understanding key characteristics of artificial intelligence
Let’s talk about the key characteristics of AI that make it unique and, if combined with increasing blockchain adoption, can change the world to become a better place to live. The critical characteristics of Artificial Intelligence (AI) are:
- Adaptive: Artificial Intelligence technology is highly adaptive, as it quickly adapts to the environment through a progressive learning algorithm. It observes the surroundings and quickly learns how to do better.
- Data ingestion: AI is used for analyzing the enormous amount of data spread over billions of records.
- Reactive: Unlike traditional applications, AI-based systems are highly reactive as they respond to the changing environment. AI systems are capable of invoking rules and procedures based on certain conditions.
- Automation: AI systems can automate repetitive tasks without the need for human intervention. With the help of AI technology, machines can perform actual human tasks.
Human trust in AI: The key challenges
One of the greatest physicists of the century, Stephen Hawking, said that “The development of full artificial intelligence could spell the end of the human race.”
With advancements in technology, trust has become a vital factor in human-technology interactions. In the past, people trusted technology mainly because it worked as expected. However, the emergence of Artificial Intelligence solutions does not remain the same due to the following challenges:
- Openness: AI-based applications are built to be adaptive and reactive, to have an intelligence of their own to respond to situations. Anyone can put it to good use or apply it for nefarious purposes. Hence, people have some reservations about trusting AI-based solutions.
- Transparency: One of the significant issues impacting human trust in AI applications is the lack of transparency. AI developers need to clarify the extent of personal data utilized and the benefits and risks of using the application to increase trust.
- Privacy: AI has made data collection and analysis much easier; however, the end-users have to bear the brunt, as the collection of humongous amounts of data by companies worldwide may end up jeopardizing the privacy of the user(s) whose data is being collected.
How the use of blockchain technology can increase human trust in AI
Blockchain technology can play a vital role in increasing human trust in AI-based applications by increasing transparency and trust in the following ways.
One of the most significant challenges AI developers face is that people always doubt how and when AI-based applications will use their data. On the other hand, no one can access data without the user’s permission in blockchain-enabled AI applications. Users can license their data to the AI application or the provider using a blockchain ledger based on their terms and conditions.
Data privacy and security
The distributed form of data sharing can play a huge role in reducing the trust deficit in AI applications. Data is highly secure as there is no central point malicious actors can attack. Moreover, distributed ledger offers more transparency and accountability of real-time data as it is available to all participants concerned.
Consensus and decision-making
One of the critical characteristics of Blockchain technology is consensus-based transactions. Every decision made needs to be agreed upon by all parties involved, and it becomes highly impossible for unauthorized access or tampering of data without the users’ consensus.
Decentralization and data distribution
There is a colossal mistrust amongst people regarding data governance, including data collection, storage, and usage with AI. With blockchain technology, AI applications can store their data in a distributed and decentralized environment. One can effectively use Distributed Autonomous Organizations (DAOs) and Smart Contracts for data governance and distribution.
One of the biggest challenges in AI-based applications is how data integrity is maintained over time. In traditional applications with a client-server architecture, data is collected from clients and stored in a centralized server. With Blockchain technology embedded into AI applications, duplication of information is avoided to a significant extent. Complete transparency, traceability, and accountability make data more actionable.
While AI can provide real-time analysis of enormous amounts of data, an AI system coupled with blockchain technology can provide a transparent data governance model for quicker validation amongst various stakeholders through smart contracts and DAOs.
Blockchain benefits can address AI’s shortcomings
Applying the benefits of blockchain technology can help address various shortcomings of AI and help in increasing people’s trust in AI-based applications. With Blockchain, AI applications acquire the qualities of decentralization, distributed data governance, data immutability, transparency, security, and real-time accountability. Many AI-enabled intelligent systems are criticized for their lack of security and trust levels. Blockchain technology can essentially help in addressing the security and trust deficit issues to a significant extent. Enormous challenges remain for both blockchain technology and Artificial Intelligence. Still, when combined, they display tremendous potential and will complement each other to restore the trust factor and improve efficiency at large.
Originally published at Venturebeat