Agadmator, one of the most popular chess channels on Youtube, got suspended in 2020. The reason “AI cybercops of YouTube discovered words ‘Black’ and ‘White’ in their content in the context of ‘Attack’ and issued a suspension on the grounds of racism.”
The scenario sounds hilarious that something perceived as smart could be so stupid. Moreover, it makes us wonder whether the idea of Artificial Intelligence is in actuality oxymoronic.
Several advocates of the technology would claim that such scenarios are just a consequence of the developing stage. According to them, it is constantly evolving and learning. But the reality yet remains perceptual.
Artificial Intelligence in Business
Today’s influx of AI advances would not have been conceivable without the convergence of three factors: the re-emergence of a decades-old AI computation model—Deep Learning, the advent of powerful Graphics Processing Units (GPUs) for complex computations, and the rise of Big Data.
According to a 2018 McKinsey Global Institute study, by 2030, around 70% of companies will have implemented at least one type of AI technology. Deep learning, on the other hand, has yet to demonstrate a strong ability to assist machines with reasoning, a skill that they must master to improve many AI applications.
Several innovative Artificial Intelligence initiatives in various sectors such as finance, business, marketing, security, healthcare, automation, etc., are generating promising market trends. These advancements are realigning the world and changing people’s perceptions of technology.
Some of the most recent Artificial Intelligence innovations that are currently trending in 2021 include:
Intelligent Process Automation (IPA)
Businesses can utilize Artificial Intelligence’s feature of Intelligent Process Automation to automate unstructured data processing. IPA is used in the banking and financial industries alongside other technologies such as Cognitive Automation, Machine Learning, and Robotic Process Automation. Investment bankers use IPA to detect discrepancies in data collection that are nearly undetectable by humans.
AI in Smart Money In 2018, Deloitte conducted a study that provided various metrics demonstrating the seamless integration of AI in the financial services industry.
1. Natural Language Processing (NLP) is now used by 60% of businesses
2. Machine learning is actively used for business solutions by 70% of the firms surveyed
3. Around 49% of pioneers in AI integration have an entire AI adoption plan in place
4. The 45% of AI pioneer companies have more than $5 million budget for AI projects
Virtual Assistants and Chatbots Voice assistants, including Google Assistant, Siri, and Alexa, are software applications that use NLP, AI, and Speech Recognition to perceive and react appropriately to a user’s verbal commands.
On the other hand, Chatbots are programs developed to help a user 24 hours a day, seven days a week, by responding correctly and answering any queries the user may have. Most Chatbots and Virtual Assistants have pre-programmed response processes that respond based on specific rules and patterns, courtesy of AI optimization.
Processors AI-enabled processors or chips are available from various manufacturers, including NVIDIA, AMD, and Qualcomm, and contribute to enhancing all business operations. These chips are utilized in functionalities such as facial recognition and object detection. Biometrics are widely used in many devices nowadays as they improve security and restrict access privileges to only registered users.
Quantum AI Artificial intelligence has played a critical role in the advancement of Quantum Computing. Quantum AI refers to the use of quantum computing to calculate machine learning algorithms. This can help with data analysis and processing by allowing the pattern to be quickly captured. Quantum AI is, therefore, substantially transforming the banking and healthcare industries.
As all company’s key databases, including financial records, strategies, and private records, are stored online, every company needs internet security. To reduce cyber risks, it also analyses Big Data and improves the system. As a result, detecting discrepancies in operations and records.
Robotic Process Automation (RPA)
RPA has the ability to handle and automate repetitive tasks. RPA is widely used in the insurance industry, but by integrating AI into standard insurance RPA procedures, automation can access and process claims with minimal assistance.
Artificial Intelligence Future
Eventually, experts plan to develop future AI systems that can do more than simulate human patterns of thinking, such as reasoning and perception—they envision it accomplishing an
entirely new line of thinking. While this is unlikely to happen in the next phase of AI innovation, it is in the spotlight of AI thought leaders.
Nonetheless, based on the McKinsey & Company simulation, AI has the potential to deliver a surplus of $13 trillion in global economic activity by 2030, which is approximately 16 percent higher than today’s cumulative GDP. This equates to an extra 1.2 percent GDP growth annually. If this possibility is realized, it will be parallel to the impact of other general-purpose technology solutions throughout history.
AI can widen the digital divide between countries. As AI adoption rates differ widely, countries may require different approaches and feedback. Leading AI regions could reap a 20 to 25 percent surplus in net economic profits compared to today while developing countries could reap only 5 to 15 percent. Many developed countries may have no choice but to shift to AI to obtain increased productivity growth as their GDP-growth momentum slows—in many instances, partially due to the issue of aging populations.
With AI destined to take over a rising number of industries, it’s essential to stay up to date on this exciting emerging technology so you can maximize your productivity for your business. Business innovation is the process of introducing new ideas into your company wherein AI is a novel concept worth considering.
On a Concluding Note.
Is AI an oxymoron? The question that started this whole conversation now concludes on the inference that AI is a nascent technology that is rapidly adapting to several industries. Just like a toddler grasping and mimicking knowledge quickly and yet not understanding the intricacies of human subtlety. AI is going to take its time to evolve.
Although the technology might not completely be smart or dumb, it is evolving within the boundaries of technological advancement and human skill sets. We cannot entirely blame its stupidity on it. To fairly judge the oxymoronity of this technology, we might need to let it develop considerably before prosecuting AI.