AI has impacted industries from the medical to education, and the legal world is no different. But as I take a closer look at the impact of AI in my part of the legal world, I see it as useful but limited. Our firm uses some AI products to generate predictions regarding the examination of patent applications, such as what classification of invention or technology type the application will receive at the USPTO. This is a useful way to check that we are communicating important aspects of inventions effectively and helps us predict how the examination is likely to proceed. It is not perfectly accurate, but is accurate enough to be helpful and requires a lot less effort than the more manual approach we used before.
We have also explored the ability of AI to produce initial drafts of legal documents. While it is true that working off an existing draft can often be more efficient than writing it from scratch, a pretty crucial step in writing a legal document is to think about the structure of the document and use that thinking to organize the writing. Language-based AI is especially challenging to simulate, and the industry might not be there yet. Currently, AI does not help very much with certain kinds of legal writing.
AI interests me both as the subject of the inventions I work with and as a potential consumer of AI. In the former case, it is clearly becoming increasingly ubiquitous in everyday life. Much like the proliferation of microcontrollers and other low-power processor devices in the Internet of Things, AI has increasingly been working in the background and under the hood in all kinds of mundane, everyday activities, frequently without the awareness of the people who benefit from its use.
In the legal profession, I am excited about the ability of AI to enhance legal research by locating documents or passages of relevance to a topic of interest. This is something that conventional keyword searching does not perform adequately, as the semantic relationships to be discovered are more subtle. Use of vectors to find related terminology is currently enhancing some of the more sophisticated search algorithms, but what will really help will be algorithms that can search by concepts as opposed to semantics.
As with every other advance in automation, it is not clear yet what impact this will have on employment and careers. I’d say a big concern is that AI could be used to produce superficially passable legal work at discount prices. Such output might appear, particularly to customers who are not well-versed in the law, to perform its function adequately, but may have hidden flaws that, absent responsible review by skilled practitioners, might not be discovered until it is too late. What, for instance, will stop an unscrupulous lawyer from contracting to produce many wills or trust documents, use an AI platform to crank them out with little or no oversight, and pass the result off as his or her work? In that case, many of the documents’ efficacy would not become apparent for years or decades and could lead to contention or loss long after our enterprising huckster has retired to a remote island.
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While the presence of IoT looks great, its future looks even better.
And more than just a concept that every tech-savvy person enjoys today, it’s also a door of opportunity that needs to be knocked, especially by the startups and other small businesses.
If IoT is to be the future, and it definitely looks to be playing an extremely important role in the coming days, one thing it will bring is more efficiency to the system.
Any and every system out there and small businesses won’t be an exception.
There are still businesses out there that are acquainted with the term IoT, and it’s a serious cause for dismay, for this is absolutely the next big thing in making.
As far as any business is concerned, the data and analytics play a huge role.
Enabling transformational benefits for businesses
The formative systems of AI were only competent in managing a narrow category of tasks. They could not scale well and often called for human intervention. However, continuous studies and progress in technology have led to the evolution of AI in tandem with IoT concept which has given rise to the much loosely used term now, Smart Machines. Leveraging the power and capability of AI, smart machines will simplify the tasks by performing them in minutes which otherwise would take weeks or even months to complete. These machines will radically transform the way most enterprises do business, bringing in an advanced level of comfort and convenience.
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The synthesis of the two concepts offers real value proposals in the form of smart sensors that seek to proffer real-time data and feedback to make these three significant analyses.
Predictive: Predictive analysis helps to determine when a part of the machinery is most likely to experience a breakdown. Such analysis will help in averting the failure through preemptive intervention.
Prescriptive: Prescriptive analysis offers immediate suggestions that can be instrumental in preventing any kind of disasters or botches.
Adaptive/ autonomous: Constant data feeds from sensors can help the systems in taking frequent actions autonomously without any human involvement.
The market for technologies like artificial intelligence (AI) is flourishing.
Many internet giants and startups are racing to acquire AI; there is a significant increase in investment and adoption by organizations.
As enterprises view business intelligence, AI is transforming their way.
Currently, artificial Intelligence includes a variety of technologies and tools, some time-tested, and the rest are relatively new.
Here are technologies that define Artificial Intelligence.Read more: click here
Mailing and access to trillions of data were the prime functions of the internet that we got introduced to.
It is this very concept of programming that led to the invention of AI [Artificial Intelligence].
But it is not limited to the financial sector only.
IOT will help in transmitting information, while AI will analyze that information, process vast calculations and make basic decisions for a business, government, etc.
This allows the company to avoid health issues originating from severe work stress, thus ensuring better performance and efficiency.
However, There Is A Downside To It- Employment
