AI, an effective tool for Indian Judiciary System  : CII Summit and Expo on AI Application & Digi-Tech

Day two of Confederation of Indian Industry’s (CII) Summit and Expo on AI Application & Digi-Tech, kick started with a thought-provoking panel discussion on AI in Public Service. The session highlighted the benefits of AI interventions in Agriculture, Smart Cities, Healthcare, Skilling, Education, Public Utility Services, Judiciary and Governance.

Mr. Sameer Dhanrajani, CEO, AIQRATE said that in India we are seeing a great opportunity for AI to support various processes both in the public and private entities.  One of the areas where AI can be most effective is in the country’s judicial system. Currently we have 33 million legal cases pending in India. 84% of which has an average pendency of 13 years.  AI can be used to deal with all previous cases that we have in our repository by extrapolating it by means of text-mining, multilayer perceptron (MLP) and deep learning. Leaving the legal system to focus on their core job, which is to solve and close cases on an agile basis.

Globally, AI has seen $45 to $58 billion investment during the last year. It is growing at the fastest pace of any exponential technology. The AI segment will be worth over $100 billion by 2025. This gives ample indication of the scale and opportunities in this sector. According to Mr. Dhanrajani, the companies that have adopted AI will take away $1.2 trillion worth of business from their competitors. In 2019 alone AI startups have received $14 billion investment across 600 funding events.

Realizing the importance of AI currently, 28 nations around the world are curating or drafting AI policies and strategies. India is one among them however where the country lags behind is in research. In India we have only 2000 to 2500 research papers submitted every year and China has 10 times more. Out of 34.8 million students coming out of our higher education system in the country only 18% are employed. The job opportunities in the new age will require skills that are not taught in our educational system and this needs to change.

India is uniquely poised to be a global leader in AI, and this is due to the diversity of our population generating a diverse set of data. Attaining a premier position in AI will require convergence of all stakeholders.   Towards this, India need to focus on 3 broad areas i.e. Education – infusing new age courses and adapting personalized learning powered by AI, Enable – create an open innovation platform, a pipeline of AI centric solutions and their adoption and Ethics – Draft an operating framework within which AI can be developed, Mr. Dhanrajani elaborated.

The panel discussion highlighted the sectors in India where AI can make the most difference:

• Agriculture – AI holds the key to unlock massive value from India’s agrarian economy by leveraging data to better predict and improve farm yield, speeding up agricultural finance, crop insurance, Kisan help centres and helping predict demand for agricultural produce. I.e. AI sensors in ponds help farmers to gain maximum value from shrimp farming through predictive maintenance.
• Smart Cities – AI driven interventions can add substantial value in analyzing local intelligence to improve traffic conditions and providing predictive intelligence on infrastructure development. It can be used to decentralized and decongest major cities and play a key role in predictive maintenance activities.
• Skilling – Utilizing AI to predict demand for skills and equip educational institutions with insights to train the future workforce.
• Swachh Bharat – AI and specifically computer vision can help substantially improve the success of Swachh Bharat. AI is already being used in the campaign in a big way. There is a WhatsApp number outside every sanitation facility. The user can send photographs of unhygienic conditions without providing any details. The photo will be processed at a central command centre and a call will be made to the vendor within 45 seconds to fix the facility. This is all being done at a cost of Rs 2 crores a month only.
• Healthcare – India’s high and diverse population makes it fertile ground for population health studies. AI can be employed to provide evidence-based treatment options and analyzing clinical notes to suggest a treatment procedure.

Governance – AI can power several governance initiatives ranging from security threats, RTI, potential fraud and corruption to improving the legal system, curbing human trafficking and tracking of missing persons.

Ms. Aparna Gupta, Analytics & Data Science Leader, Oracle Cloud Solutions Hub; Mr Kapil Gandhi, Vice President – Strategy – Intelligent Automation, Genpact Digital; Ms. Padmashree Shagrithaya, Vice President & Head – Analytics, Data Science and Visualization, Capgemini; Mr Sanjeev Kumar, Sr Director Data & Analytics, Baker Hughes; Mr Satyamoy Chatterjee Executive Vice President Analyttica Datalab Inc also participated in the panel discussion chaired by Mr. Sameer Dhanrajani.

With an objective of identifying and showcasing the best Start-up with the most Innovative scale deployment of Artificial Intelligence & Industrial AI in a large corporate environment CII in association  with Accenture Ventures held the ”CII AI Challenge” which felicitated the best startups in each of the segment.

AskSid has been recognized as the Best Start up for Innovative deployment of Artificial Intelligence in large scale corporate environment.

Qualitas Technologies has been recognized as the Best Start up for Innovative deployment of Industrial AI in large scale corporate environment.

The summit witnessed a live audience poll for the presentation made by the Start-ups and  Orbo.ai was recognized has Best Start up (Audience poll category ).

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Regardless of industry, it seems that nearly every business is asking the same question nowadays: How can artificial intelligence help us?

Google Trends data shows that searches for “machine learning” — a common application of AI that enables machines to process and learn from data inputs — have skyrocketed over the last several years. It’s clear that businesses are eager to get their hands on this technology, which promises to increase efficiency and productivity.

Of course, with all the hype around AI and machine learning comes a few key misconceptions about how it can be implemented and leveraged. We asked members of the Forbes Agency Council to help clear things up and explain some realistic, beneficial ways agencies can use AI.

1. Improve Team Efficiency 

Besides AI ad tech, which is still a developing space, using AI to help company talent get their projects done faster and better has been our greatest benefit so far. In the interim, we are able to learn more about how AI, natural language processing, machine learning and big data tools interact internally before applying externally in the wild with a good sandbox environment. – Sunny Patel, TRENDS DIGITAL – Social & Digital Advisory for Corporates

2. Enhance Customer Communications 

Chatbots leverage natural language processing, simulating a live chat experience and allowing customers to have a conversation with the brand. Infinitely more cost-effective than staffing a 24-hour customer service team, the AI programs answer customers’ questions and serve up the relevant response in a conversational way. – Keri Witman, Cleriti

3. Understand Breaking News And Its Sources

The best use of AI today is in understanding breaking news and information, and the source of information. That knowledge should be used to better understand how those key constituents engage and their preferred content formats. This enables a level of personalization and relationship-building that can be used to sell products, forge relationships and build brands. – Peter Prodromou, Racepoint Global

4. Streamline The Customer Experience 

As a brand experience company focused on live programs, we’ve used AI to create voice-activated content for audiences attending live events, conferences and tradeshows. Session content, wayfinding and FAQs can all be programmed in and activated by attendees who ask questions and get customer responses. This type of application can translate to any point-of-purchase scenario. – Chris Cavanaugh, Freeman

5. Personalize Content And Delivery 

One way that we leverage artificial intelligence is through predictive data on the consumer to personalize marketing initiatives. You can leverage data about when consumers most frequently engage with email, what content is most beneficial to them, what channels they are most likely to engage with and much more, to help personalize their unique buyer’s journey. – Elyse Flynn Meyer, Prism Global Marketing Solutions

6. Optimize Your Ad Campaigns 

Programmatic advertising is a good example of AI application. Algorithms are used to analyze online behavior so that advertising campaigns can be optimized to maximize conversions. Using AI platforms, we can learn very quickly about the best combination of copy and creative that works across Google and social media platforms. – Alannah Tsimis Sandehl, IDM Brand

7. Streamline Small, Appropriate Components Of Your Processes 

The problem I see with bots and AI is that everyone is trying to automate the entire process. Instead, I suggest taking small components and using AI to make it easier or streamline that one piece. The “out of the box” AI platforms are not one-size-fits-all solutions. – Gary Henderson, DigitalMarketing.org

8. Analyze Data Better 

When people say “AI,” they really mean machine learning. Unsurprisingly, machine learning is best used in analytics platforms at most agencies, where it can attribute value to different pieces of content, contribute to social listening, identify trends and key messages, words or phrases, which help determine how well a company’s positioning sticks. – Kathleen Lucente, Red Fan Communications

9. Predict Content Performance 

One way to leverage AI is to help predict branded content performance. Advertisers should no longer go with their gut when choosing marketing messages that’ll resonate with consumers. By merging the art and science of content creation, marketers are now able to make strategic decisions that deliver measurable results, even when it comes to something as seemingly subjective as a brand’s creative. – David Shadpour, Social Native

10. Improve Decision-Making 

Right now, artificial intelligence is best at deciphering large amounts of data sets and making pre-programmed decisions based on the results of the input. In this regard, the AI algorithms are far faster than the human brain. The best use of AI is to compile, decipher, record and execute decisions based on large amounts and a variety of metrics. – Ernesto Carrizoza, Movement Marketing

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The global energy industry is facing fundamental shifts in the way it generates, sells and distributes power. The pressure is on to cut carbon emissions and, as a result, methods must be found to manage the increasing gigawatts of unpredictable, weather-dependent renewable energy flowing on to power grids. The cost of electricity is also a concern, not just for consumers, but for governments keen to keep their voters happy.

In short, there is a global demand for clean, cheap, reliable energy – and artificial intelligence (AI) is increasingly being used to help meet this need. Enabling the growth of low-carbon, green electricity is an AI application with a potentially huge long-term impact.

Renewable forms of electricity are emerging as the successors to traditional coal and gas-fired power plants. A key problem with renewable electricity, however, is its inconsistency. A cloudy day or a string of calm, windless afternoons will cut generation and can create power shortfalls. Conversely, too much energy can be generated; in March this year, for example, a sunny, windy Portugal produced more renewable electricity than it consumed.

At present, this means backup forms of power, which can be switched on quickly, often dirty diesel generators or coal plants, are used to smooth out the troughs and costly storage solutions are required to manage peaks of excess generation.

Using AI to forecast and make energy-saving decisions 

Aidan O’Sullivan, head of University College London’s energy and AI research, says using AI to create “forecasts for electricity demand, generation and weather can lessen the need for these backup mechanisms”, by predicting and managing fluctuations in production.

AI research is also investigating decision-making with a “scale and complexity that begin to exceed that manageable by a human operator”, he says. For example, AI could be used to manage electricity shortfalls by briefly switching off power demand across entire communities or regions. “This might be thousands of refrigerators in people’s homes or large sites of demand, such as industrial plants,” he explains. “The speed and complexity of this task requires advanced AI.”

The speed and complexity of this task requires advanced AI.

Ceding control of your home to a remote AI might seem like the stuff of science fiction, but the integration of AI into our appliances is already underway. For example, AI is being used to manage energy use in a device most of us use every day – mobile phones. The latest iteration of Google’s Android phone operating system includes a function which studies your app habits to ensure battery is deployed only on the ones you like the most. Meanwhile, rarely used apps, which would previously hum away in the background consuming power, are shut down.

AI can now also work out how much electricity each of your home appliances is using, too. UK startup Verv uses AI to find the “fingerprint” of each appliance, using data from your electricity meter. Home appliance manufacturers will come under increasing pressure to produce energy-efficient products. With access to exactly what it costs to run a dishwasher or TV, consumers could rapidly become disenchanted with power-hungry devices.

Giving consumers foresight over their energy profile

Dr O’Sullivan says the proliferation of virtual assistants in homes, combined with such data, could fundamentally disrupt the way we buy and use electricity. “The integration of energy data with products like Alexa and Google Home may lead to AI home energy management systems where, for example, rather than turn on your washing machine yourself, you schedule it to run when the electricity price is going to be lower.”

Businesses can also benefit from such advances. British AI developer Grid Edge has created technology which enables firms to control energy use in their buildings, making the most of low-demand, cheaper periods of electricity supply. As a result, companies can receive payments from the National Grid for taking strain off the grid at peak times. Chief executive Tom Anderson says: “The use of AI, in our case predictive machine-learning algorithms, enables the consumer to have foresight over their energy profile for the first time.”

This means energy providers could find themselves running to catch up with increasingly sophisticated customers, changing the power dynamic between supplier and consumer. Mr Anderson says the next frontier for AI and energy will be about “reshaping the relationship between consumer and supplier”. He predicts peer-to-peer markets for sharing electricity and “prosumer” models, where consumers generate and sell their own power, will multiply.

Relying on AI could leave energy networks vulnerable to cyber attacks

Passing the reins for energy networks to AI means new risks can emerge. Dr O’Sullivan cautions: “As the grid becomes more automated, it becomes more susceptible to cyberattacks. One area we are interested in is using AI to defend the grid and minimise damage from targeted attacks.”

Another risk is the potential for customers’ data to be exposed. Google’s Android app algorithm, for instance, will build datasets from your behaviour patterns, although Google says this knowledge will be stored solely on your device.

Dr O’Sullivan concedes that data privacy is a big concern. “There is the potential for people to infer all sorts of information from energy data, from occupation patterns even to religion,” he says. “Beyond that, there is the socio-economic concern this technology might benefit only those who can afford it and trap those who can’t in a more costly energy system.”

The use of AI enables the consumer to have foresight over their energy profile for the first time

Despite these risks, Mr Anderson is positive about the future of AI and energy. He says the data such technology provides will empower, not restrict, electricity users. AI, he argues, enables citizens to question and work out “what is best for me from a comfort, carbon and cost point of view”. With such a proactive approach, the consumer can begin to be better informed and empowered in how they chose to engage with the wider energy system around them.

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Advances in computing power, the sheer volume of data that is now available online and improved artificial intelligence algorithms have finally made AI practical. But how should you implement artificial intelligence data storage?

There is no one-size-fits-all answer for artificial intelligence data storage. Every AI application is different and so is the data that is associated with the application. As such, there are a number of different questions that you must consider when planning AI data storage.

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