ABBYY, a Digital Intelligence company, today launched a global initiative to promote the development of trustworthy artificial intelligence (AI) technology. As AI becomes ubiquitous across consumer and enterprise high-value and large-scale uses and more open source tools become available for digitizing data, the ethical use of accessing and training data is imperative.

A growing number of technology leaders expect fair, transparent and ethical AI systems in order to fuel the continued adoption of AI and spur innovation. In fact, by 2025, Gartner estimates 30 percent of large enterprise and government contracts for the purchase of digital products and services that incorporate AI will require the use of explainable and ethical AI. Furthermore, three-fourths of consumers say they won’t buy from unethical companies, while 86% say they’re more loyal to ethical companies. Therefore, ABBYY made public its core guiding principles on developing, maintaining and promoting trustworthy AI technologies and advocates for other technology leaders to do the same.

“Innovation and ethics go hand in hand. As the use of AI proliferates, it is important for technology leaders to adhere to and promote the utilization of technologies that are transparent, fair, unbiased and respect data privacy,” commented Anthony Macciola, Chief Innovation Officer at ABBYY. “By adhering to high standards with regards to the performance, transparency and accuracy of our products, we are able to deliver solutions that have a tremendous impact for our customers.”

• ABBYY, whose Digital Intelligence solutions leverage AI technologies including machine learning (ML), natural language processing (NLP), neural networks, and optical character recognition (OCR) to transform data, affirmed its commitment to the following principles and advocates for other leading technology organizations to also commit to trustworthy AI standards:
• Incorporating a privacy-by-design principle as an integral part of its software development processes
• Protecting confidential customer and partner data
• Developing AI technologies that meet or exceed industry standards for performance, accuracy and security
• Empowering customers and partners to successfully implement digital transformation in their organizations by delivering solutions that provide a greater understanding of content and processes
• Providing visibility into the performance characteristics and metrics of its technologies, as well as providing opportunities for product feedback
• Delivering AI technologies that are socially and economically beneficial
• Fostering a culture that promotes the ethical use of AI and its social utility

“AI has the power to yield significant social and economic benefit,” continued Macciola. “With ethics in mind, we have the ability to transform the future in a manner that promotes innovation, accelerates technological advancements, and augments human intelligence, creativity, and capabilities responsibly.”

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As most people are now aware, the Union Budget 2020 is going to be announced by the Central Government on 1 February 2020. While several expectations are being expressed by industry leaders, professionals as well as students, what the government actually takes into consideration can only be determined next week when the budget is issued. In the meanwhile, industry expectations on the Union Budget 2020 continue to pour in.

Dr. Ranjit Nair (PhD AI), CEO and founder of Germin8, a digital intelligence company feels that owing to the potential artificial intelligence has in India, a special impetus must be given to it. “One of the biggest areas where countries are vying for dominance is Artificial Intelligence, which is expected to have a huge impact not only in commerce but also in areas like health, national security, cybersecurity, food security, education, and global warming. Unfortunately, countries like USA and China are leaving India behind in terms of AI research, AI entrepreneurship and government investment in AI,” he says. Along the same line, he expects the government to take the following measures in the field of artificial intelligence (AI):

Artificial Intelligence grand challenges

The government can announce AI grand challenges that are open to teams from academia and industry that involve solves an important problem for India. The government’s role in this would be to give a crisp problem definition, provide access to the data and of course provide a good cash prize. Such AI grand challenges will result in important problems getting solved, new startups and jobs, and capture the nation’s imagination and give an impetus to the field of AI.

Make it easier to access capital

One of the biggest challenges that startups face is early-stage funding. The government could announce a fund on the likes of Singapore’s Temasek that will invest only in early-stage Indian AI startups. Also, the government could announce lower long term capital gain’s tax for investing in AI-based startups. This will encourage more angel investment into AI start-ups.

Improve Artificial Intelligence talent in the country

While there are a lot of engineers being produced in India, we still lag behind other countries in terms of the number of AI PhDs and AI research. The government should make more research grants available for AI research and should also offer incentives to institutes that invest in AI training.

Ease of doing Business

The government’s focus should be on bringing policies that encourage AI companies. There should be less red tape, more freedom from the government departments so that entrepreneurs can be focused on building solutions without unnecessary distractions.

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Machine learning is gaining popularity to deal with increasingly complex data and analysis problems. Many projections also point that the highest growth is in India IT spending in software and IT services for 2017. This includes building new digital platforms with Machine Learning at the center. IBM continues to be at the forefront of it all.

‘Machine Learning’ termed by an IBM decades ago has evolved significantly. Today, it enables enterprises to drive critical insights. Businesses are increasingly using machine learning to support advanced analytics across a growing range of industries and initiatives. With India’s focus on digitization, it’s an apt time for organizations to make this transition.

Prasanna Keny, Senior Technical Manager, IBM India says that going forward, machine learning is going to be an imperative and not a choice.“According to a Harvard study 72 percent of organisations are vulnerable to disruption due to digitization and data intelligence. For the respondents, 29 percent of organisations said they are extremely susceptible to market disruption while about 43 percent responded they are significantly susceptible due to the digital intelligence and machine learning used by their competitors. That is how important machine learning, analytics, deep learning or artificial intelligence has become in terms of competition and the ability for an organisation to maintain the leadership position,” said, Keny.

Citing various examples Keny explained the use cases of machine learning. He said it can be used for customer analytics and fraud combating.“A use case of analytics and machine learning is for countering fraud. When we think of fraud, the image that crops up in our mind is online payment fraud. But this can be used in a variety of cases. For instance, we have customers using it for expense fraud, procurement fraud or in case of insurance fraud detection for claims,” added Keny.

However, the whole process or the journey of machine learning involves challenges as well. Some of the challenges are data management where there is unavailability of prior data, the evolving environment and toll sets users, difficulties in collaboration where multiple people are working together and operationalizing.

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