AI What we've seen so far NZ Conference V2...based on machine learning, here are seven of the top AI...
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Artificial Intelligence What we’ve seen so far in 2019, what is to come…and how can it assist personal and financial wellbeing? Implementation of artificial intelligence has risen significantly in the last year, impacting platforms, tools and applications around the world, in fields as diverse as healthcare, retail, agriculture and more. As an increasing number of industries begin opting for solutions based on machine learning, here are seven of the top AI trends that we have seen in 2019 and a prediction of what we think will come in the near future: 1. AgTech Startups and incumbents are embracing crop monitoring AI to manage pesticides, detect and target weeds, and forecast how weather changes impact agriculture. With the help of AI, farmers can evaluate a variety of factors in real time, including weather conditions, temperature, water usage and soil collections, to better inform their decisions. Using drones, AI-enabled cameras capture images of an entire farm and analyze them to identify problems and areas for improvement. Unmanned drones are able to cover more land in a shorter period of time than humans on foot, allowing for large farms to be monitored more frequently. As the data is being gathered, we expect increasing focus on data governance, as well as monetization efforts. Companies will look to establish and drive strategic partnerships that include frameworks for the sharing and exploitation of aggregated data and analytics. 2. HealthTech Fast-track regulatory approval for AI software products has opened up new commercial pathways for AI imaging and diagnostics companies globally. On the consumer side, image recognition technology is helping turn smartphones into powerful at-home diagnostic tools, giving more people access to health advice – and faster. Navigating the requirements of privacy and data security laws will continue to complicate the requirements for companies looking to innovate in the “healthtech” area, especially startups that are still getting familiar with the regulatory framework. 3. Autonomous vehicles Self-driving cars are not a practical possibility without Internet of Things (IoT) technology working closely with AI. The cars use sensors enabled by IoT to collect data, and the programs used for decision-making are powered by AI models. AI algorithms then make decisions and take action using the data collected. Key features include path planning, which enables the car to find the best route from point A to point B; eye-tracking, which monitors where drivers are looking and warns those who are distracted or not paying attention to the road; and natural language processing, which enables the car to follow voice commands. Autonomous vehicles could also have the ability to communicate with each other, allowing for optimization of traffic as a whole. As regulation of self-driving cars continues to The use of bots as customer service agents is revolutionizing relationships between companies and their clients.
Transcript of AI What we've seen so far NZ Conference V2...based on machine learning, here are seven of the top AI...
Artificial IntelligenceWhat we’ve seen so far in 2019, what is to come…and how can it assist personal and fi nancial wellbeing?
Implementation of artifi cial intelligence has risen signifi cantly in the last year, impacting platforms, tools and applications around the world, in fi elds as diverse as healthcare, retail, agriculture and more.
As an increasing number of industries begin opting for solutions based on machine learning, here are seven of the top AI trends that we have seen in 2019 and a prediction of what we think will come in the near future:
1. AgTechStartups and incumbents are embracing crop monitoring AI to manage pesticides, detect and target weeds, and forecast how weather changes impact agriculture. With the help of AI, farmers can evaluate a variety of factors in real time, including weather conditions, temperature, water usage and soil collections, to better inform their decisions. Using drones, AI-enabled cameras capture images of an entire farm and analyze them to identify problems and areas for improvement. Unmanned drones are able to cover more land in a shorter period of time than humans on foot, allowing for large farms to be monitored more frequently. As the data is being gathered, we expect increasing focus on data governance, as well as monetization eff orts. Companies will look to establish and drive strategic partnerships
that include frameworks for the sharing and exploitation of aggregated data and analytics.
2. HealthTechFast-track regulatory approval for AI software products has opened up new commercial pathways for AI imaging and diagnostics companies globally. On the consumer side, image recognition technology is helping turn smartphones into powerful at-home diagnostic tools, giving more people access to health advice – and faster. Navigating the requirements
of privacy and data security laws will continue to complicate the requirements for companies looking to innovate in the “healthtech” area, especially startups that are still getting familiar with the regulatory framework.
3. Autonomous vehiclesSelf-driving cars are not a practical possibility without Internet of Things (IoT) technology working closely with AI. The cars use sensors enabled by IoT to collect data, and the programs used for decision-making are powered by AI models. AI algorithms then make decisions and take action using the data collected. Key features include path planning, which enables the car to fi nd the best route from point A to point B; eye-tracking, which monitors where drivers are looking and warns those who are distracted or not paying attention to the road; and natural language processing, which enables the car to follow voice commands. Autonomous vehicles could also have the ability to communicate with each other, allowing for optimization of traffi c as a whole. As regulation of self-driving cars continues to
The use of bots as customer service agents is revolutionizing relationships between companies and their clients.
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evolve across the regulatory spectrum, we expect the market and negotiating positions between suppliers and buyers of technology to evolve around issues such as warranties and liability.
4. Customer serviceWe’ve written about robo-advice tools in another of our updates. We’ve also seen that the use of bots as customer service agents is revolutionizing relationships between companies and their clients. AI-powered chatbots can interact with customers, identify consumer needs and ensure that inquiries are directed appropriately. The relatively low cost of chatbots, compared to traditional customer support, makes implementation attractive to many companies. AI has also proven to be useful in customising user experiences. Some companies are using AI to analyze customer data and tailor products to their users, as well as to provide interactions aimed at increasing customer engagement and driving up sales. Privacy and data security considerations continue to impact this space. As the opportunities to use AI to supplement or replace human interaction increase, the employment considerations are likely to be an increasing focus.
5. Facial recognitionFacial recognition helps businesses provide more personalized services to their customers. Early commercial applications are taking off in security, retail and consumer electronics, and facial recognition is quickly becoming a dominant form of biometric authentication as the accuracy and reliability of the technology continues to increase. However, the regulation of facial recognition technology may impact widespread adoption.
6. Fraud preventionAI-based fraud prevention relies on a combination of supervised and unsupervised machine learning. The technology takes into account emerging activities, behaviors and trends in transaction anomalies, making it possible to thwart more sophisticated attacks. AI also provides fraud analysts with real-time risk scores and greater insight into where best to set threshold scores to maximize sales and minimize fraud losses. Where decisions are made based on these scores, being able to provide assurances that the decisions are being made without any indicia of bias will become increasingly important.
With the help of AI, digital businesses are able to gain greater control over chargeback rates, decline rates and operations costs. Businesses selling virtual goods, such as gaming companies, can provide a more consistent, high-quality user experience.
This fast moving space is only going to get better.
Alasdair McBethPartnerT: +64 4 474 3257M: +64 27 255 5735E: [email protected]
Rachel TaylorPartnerT: +64 4 474 3256M: +64 27 255 5715E: [email protected]
Tracey CrossPartnerT: +64 9 916 3773M: +64 27 255 5710E: [email protected]
Nicole MacFarlaneSpecial CounselT: +64 9 300 3891M: +64 27 209 4820E: [email protected]
At DLA Piper, we believe great business can make a better world. That’s why, every day, we help our clients succeed. Bold thinking and trusting relationships are at the heart of our work. Together, we can make business better.
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About DLA Piper
DLA Piper is a global law fi rm operating through various separate and distinct legal entities. Further details of these entities can be found at www.dlapiper.com.This publication is intended as a general overview and discussion of the subjects dealt with, and does not create a lawyer-client relationship. It is not intended to be,and should not be used as, a substitute for taking legal advice in any specifi c situation. DLA Piper will accept no responsibility for any actions taken or not taken on the basis of this publication. This may qualify as “Lawyer Advertising” requiring notice in some jurisdictions. Prior results do not guarantee a similar outcome.Copyright © 2019 DLA Piper. All rights reserved. | AUGUST 19
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