You may have heard the term “blockchain”, using the record-keeping underlying the Bitcoin network.
Whether they can cope with this task depends on how much they manage to consider all aspects of responsible AI:
- Fairness: Are we minimizing bias in our AI data and models? Are we considering the issue of bias when using ai?
- Interpretability: Can we explain how the AI model makes decisions? Can we guarantee the accuracy of these decisions?
- Reliability and safety: can we rely on ai systems to work? Are ours ai systems vulnerable to attacks?
- Governance: who is in charge of ai systems? Do we have proper control procedures in place?
What is blockchain?
Blockchain seems complicated and it definitely can be, but its basic concept is really quite simple. It is a type of database. To confirm blockchain consulting firms, you first need to understand what a database is.
Artificial Intelligence: Current Situation
To get a better understanding of how organizations are doing today, we interviewed more than 1,000 business leaders who are exploring or already implementing ai development services. Twenty percent of those surveyed said their companies are planning a large-scale introduction of ai in 2019. If these ambitious plans are realized, many of the leading companies in the United States will reach a new level of AI application, and not in specific areas, but throughout the entire operation.
How to Scale AI Solutions
Last year, we formulated eight forecasts of the likely development of ai in 2018, taking into account the consequences for consulting, government and society. The trends we identified back then (including the real impact of AI on the workforce, the need to focus on the responsible use of AI by companies, and emerging cybersecurity threats) are only growing today.
However, in 2019, as more and more AI-based solutions emerge from laboratories into offices and hospitals, factories, and construction sites and become part of consumers’ lives, a new approach is needed. We do not just indicate the likely events – we talk about what should happen in the field of AI thanks to the efforts of company leaders.
Users, Developers, and Data Mining Professionals
As AI becomes more popular, most of the company’s employees will need to undergo training in order to become users of artificial intelligence. They will learn how to use AI-powered enterprise applications, manage data properly, and seek expert help when needed.
A more specialized group (perhaps 5-10% of employees) must undergo additional training to become developers: business line specialists from among confident users who can shape use cases and datasets and work closely with AI specialists to develop new applications based on artificial intelligence.
Finally, a small but very important group of engineers and data mining professionals will undertake the complex work of building, deploying, and managing AI applications.