As technology moves forward, conversations on AI software development and its global impact are becoming more and more common these days. They range from the extremely optimistic views on the possibilities it has to offer to the fears of losing jobs and privacy.
AI has the potential to improve medical diagnoses, weather prediction, supply-chain management, transportation, and even personal choices. However, movies such as “I, Robot,” “Ex Machina” and “Terminator” show that Artificial intelligence is believed to be quite dangerous.
We’ve decided to dispel the most common illusions and myths about AI software development and shed some light on the possibilities of this disruptive technology.
Myth #1: AI solutions will replace human labour
Nowadays AI is transforming business processes by helping organizations to automate not only their basic tasks but also the most complex operations. Experts argue that AI-based software is likely to destroy jobs faster than the economy can keep up. It has the power to create an unemployed underclass that will be dominated by an elite class of “machine owners.”
Statistics show that within the next two decades around 47% of all employment opportunities will be occupied by machines.
Technologists Carl Benedikt Frey and Michael A. Osborne carried out the research where they expressed predictions on the kinds of jobs that technology is likely to replace within the next decades. For instance, middle-skill jobs of tax accountants, telemarketers, and freight agents are deemed to be replaced by robots in the next few years. Whereas creative workers such as scientists, healthcare professionals, leaders, entrepreneurs, writers, and artists are to be the most secure.
On the whole, humans are the most productive at professions that require them to regularly interact with other humans, while machines supersede them at such things as following patterns and executing routine work. Nevertheless, a huge number of professions are impossible without human involvement.
The capabilities of AI to completely replace human potential are vastly overestimated. Even the most powerful AI software is written by humans, smart AI systems are based on algorithms designed by humans, and datasets are curated and customized by people as well. Furthermore, it is particularly hard to automate a large number of jobs with AI, since almost all AI systems have a narrow focus and are designed to do only one thing perfectly.
According to the economist Daniel Lacalle, if AI technology really destroyed jobs, there would be no work today for anyone. Over the past 30 years, the technological revolution has been unparalleled and exponential, but there are even more jobs and better salaries on the global scale. For instance, the German region of Baviera is one of the developed areas with the high degree of technology adoption and robotization but it has only a 2.6% unemployment rate. And the same tendency can be observed in many other parts of the world.
So, AI software development will potentially transform some of the current jobs, but it will also help create entirely new roles and opportunities. In the future, humans and machines are likely to be working side by side, allowing us to focus more on creative problem solving and rely on AI technology for research and process functions.
Myth #2: AI software development requires heavy investments
Since AI is a complex technology, it does require deep expertise in programming languages and sophisticated algorithms. Most types of AI applications require heavy lifting by data scientists and big data engineers, machine learning specialists and computational linguists. These skills are a must for large-scale projects where artificially intelligent software is developed to make autonomous decisions, self-improve and react accordingly. These systems are usually built by global technology giants like Google which have huge investment funds and access to numerous data sources.
Nevertheless, a growing number of AI-based software tools are becoming increasingly available for business leaders. Many organizations create smart business applications developed on top of tools that Google, Apple, Amazon, and other tech corporations create. Amazon’s Alexa has already solved a complex problem of speaker-independent voice recognition, and its noise canceling technology allows using voice commands in noisy places. In a business setting, Alexa is widely used for a wide range of tasks on command, e.g. to start a meeting, control the equipment in a conference room or notify an IT department of an equipment issue. Whereas AI platforms such as IBM Watson can help you easily integrate AI into your application to store, train and manage your data in the secure cloud.
Generally speaking, a number of simple AI tasks can be tackled by developers without profound knowledge of data science. Using various tools and mathematical methods, they can implement basic AI-based components into your solution. So, if you want to use existing AI tools to address specific components of an application and configure them to your specific business needs, you will require less machine learning expertise and more knowledge of core business processes. This, in turn, will help you save costs on building huge interdisciplinary teams of data experts. However, for large-scale projects and more complex business requirements, deep expertise in data analysis, aggregation, and processing is a must.
To find out more about the latest AI solutions and top AI development vendors, read our latest article.
Myth #3: Artificial intelligence software will surpass human intelligence
“By far the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.”― Eliezer Yudkowsky
Many tech experts argue that machines will become super-intelligent and in some time will outpace human intellectual potential. Bill Gates and Stephen Hawking have also expressed concerns about “killer robots” while Elon Musk believes AI remains a fundamental threat to the existence of human civilization.
On the whole, AI applications can be split into two categories – specialized and generalized. Specialized AI solutions are focused on performing one job in one field really well. They represent the majority of AI solutions on the market, and they are not likely to take over our world. On the other hand, Google, Facebook, Amazon and other tech giants possess massive amounts of data and engineering capacities to develop a truly intelligent machine. And we can only hope that they will use it wisely.
Opinions on AI and its disruptive power differ greatly. In some aspects, AI systems already outpace humans, for example, in speed of calculations and memory recall capacity. Whereas in other aspects, like creative ability, emotional intelligence, and strategic thinking, they are still far behind and are not likely to be close anytime soon.
Myth #4: AI solutions will destroy our privacy
Many people believe that Artificial intelligence software poses a real threat to our privacy. Indeed, intelligent software solutions already take a lot of decisions for us. They tell us what we want to watch, wear, buy, who we want to communicate with. What’s more, we willingly give access to all our information. We can’t even use an app unless it gets access to all our content, photos, contacts, location, etc. Since modern AI systems are able to collect and analyze more information than traditional data processing systems, the threat to privacy is greater than in non-AI systems.
This highly controversial topic has a lot of ethical and technological implications, so it is impossible to cover it in one article. However, one thing is clear: AI software development has to be regulated to prevent any violations and GDPR has been a great step in this direction.
Also, the European data protection authorities have recently adopted guidelines on Automated Decision-making including the so-called artificial general intelligence. These guidelines are likely to greatly impact AI-based business models and privacy regulations. Additionally, a number of approaches and tools such as anonymization, PIAs, and privacy by design can help organizations ensure their AI systems comply with data protection legislation and minimize the threat to privacy.
On the other hand, by sacrificing some of our privacy, we may solve a lot of acute problems. The data collected with the help of AI and machine learning can be used for detecting cybersecurity threats, fighting crimes, and curing diseases. For instance, Barclays Africa uses AI to look for indicators of compromise across the company’s network, both on-premise and in cloud. While a US-based startup Deep Science utilizes AI to help retail stores detect armed robberies in real-time by identifying guns or masked assailants. So, with the right execution and regulations, AI can help humans fight crimes, security threats, and much more.
On the whole, the views on AI software development are polarized and controversial. Still, many experts see AI as an opportunity rather than a threat. AI technology may act as a method of augmenting human workforce and enabling us to work in newer and smarter environments rather than disrupting every single aspect of our lives. But like with any powerful technology, we need to use it prudently.