Artificial or human intelligence?
So, you are here: you have decided on the idea and concept of the startup, and have received investments. It's time to look for those with whom you will drink liters of coffee and Corvalol during crunches. And after a successful launch – it’s champagne. Or maybe save on all those drinks? During long searches and interviews, team building exercises or meetups that take up time? Maybe just go ahead and pay for a subscription to ChatGPT?
The capabilities of modern artificial intelligence are truly impressive. He will write the code, think through the marketing strategy, and file the content. So the temptation to give all tasks to neural networks is really great. But is everything so rosy? Is it true that AI technologies can replace humans so successfully that savings on employees will not bury the project, but will completely justify itself? Let's figure it out.
What qualities are important for a startup candidate?
Let's first determine what skills a member of our future team should have. And then we will understand how artificial intelligence can meet these criteria. Separately, it is worth noting the specifics of startups: there is no stability and processes that have been well-established over the years; a lot will have to be rebuilt from scratch. And there will often be nowhere to wait for help. All this directly affects the requirements for an ideal employee.
Based on our experience, we include the following qualities and skills in the list of expectations from a candidate for a startup:
→ Initiative. It is important that a person not only acts according to the technical specifications, but also can independently propose improvements, looking at the project from a new angle. The candidate must also be able to cope with the stress of uncertainty and work without clear algorithms.
→ Expertise. No one forbids taking juniors. It will be cool if a person grows with the project. But if there is no one to insure and double-check the employee’s work, then it is better to give preference to an experienced specialist.
→ Flexibility and adaptability of thinking. Sharp changes in work priorities, asap tasks, the appearance of new people in the team – this is the reality of any startup. And it should not frustrate the employee.
→ High emotional intelligence. This is about the ability to work in a team even under conditions of high psychological stress, and about the absence of fear of responsibility, and about constructive resolution of controversial or even conflict situations.
→ High self-organization. The opportunity to work slowly in the startup world is extremely rare. Therefore, an employee must be able to independently set priorities, correctly estimate the time it takes to complete tasks, and use it as efficiently as possible. In short, it will be cool if the candidate is also his own project.
It is clear that a large established company will be happy to hire a person with such a set of skills. But there, the lack of some skills can be compensated for by a work system that has been built over the years, a clear distribution of responsibilities, the presence of experienced employees, etc. But for a startup, assembling at least the core of a team of proactive, independent and responsible experts is vital.
Does ChatGPT meet these requirements?
Once we have determined the expectations from the candidate, we can check how well our virtual applicant meets them. Let's go through all the points.
Initiative
The neural network will cope with the task as successfully as you with the industrial product. She can do something cool, but only within established limits. There is a request – there is a solution.
But AI will not physically be able to fully immerse itself in your project, evaluate it entirely and offer something original. As for important strategic decisions, here all responsibility will also be entirely on you. At this point we make a choice in favor of the person. Ideally, groups of people.
Expertise
It all depends on the complexity and specifics of the task at hand. In most cases, ChatGPT does a decent job. But you shouldn’t trust neural networks 100%: someone needs to double-check the result.
Some modifications are almost always necessary. This applies to code, images, and texts. But a neural network can really replace part of the team – mainly the juniors. So in terms of expertise, humans and artificial intelligence have parity. You need both a neural network and a live qualified operator.
Flexibility and adaptability of thinking
This point is entirely up to artificial intelligence. The machine does not care that the vector and priority of tasks can change dramatically. It is available 24/7 and almost instantly produces results upon request.
High emotional intelligence
The neural network itself, of course, does not experience any psychological or emotional problems. He will even be able to give fully qualified advice on resolving a dispute within the team. Only again – everything is based on a clear request.
AI is not able to resolve misunderstandings with a customer or colleague in the moment. He will not relieve the accumulated tension with a good joke or an anecdote from life. At the same time, the psychological microclimate within a startup team is extremely important. Even if it consists of only a few specialists. Therefore, here, undoubtedly, the living person wins.
High self-organization
The speed at which tasks are completed by the neural network allows the team to breathe out. Writing a promt and then checking and correcting the result will be much faster than doing everything from scratch. It also helps free up more time to tackle other tasks or think about strategies. Yes, even for relaxation, why not?
But again it is necessary to mention that everything depends on the neural network operator. If he initially misses deadlines or forgets about some task, then the AI will no longer help with this. It is the live employee who must monitor tasks and their priority. So in this regard, in terms of importance for a startup, a person and his digital substitute are again equal.
Subtotal: pros and cons of neural networks in a startup
Of all the points that are important to us, artificial intelligence has completely eclipsed humans in only one. It seems the result is not very encouraging. Let's consolidate the results and go over the pros and cons of the neural network.
First, the disadvantages of AI, they are also the advantages of human abilities:
Initiative and creative outlook on work
Ethics and emotional support
Making strategic decisions
Responsibility for the result
Awareness and Insight
Advantages of using neural networks in a startup:
Speed and scalability
Availability 24/7 – no vacations, days off or sick leave, only pay for internet
Reducing costs for personnel performing routine work
Analysis of a huge amount of data in minimal time
Automation of a number of tasks
I would really like to imagine that the neural network will become a highly efficient and multitasking employee. Fast, creative, reliable. Almost free. Which seems to work remotely, but is always online. But the reality looks different.
For AI to show truly worthwhile results, a professional in his field must work with it. He must be able to write an effective routine and check the result for errors. Therefore, it will not be possible to completely replace people with neural networks, either now or in the near future.
What tasks in a startup can already be entrusted to neural networks?
Despite all the disadvantages, transferring some of the work into the hands of ChatGPT, Midjourney or other useful toys is not only possible, but even necessary today. Under the supervision of your living colleagues, of course. What kind of tasks could these be?
Chatbots for customer support
Most standard queries can easily be given to a neural network. She will respond at any time of the day, without making the client wait. At the same time, the level of her expertise can be quite high.
Generating text content
SEO and LSI texts, posts on social networks, email newsletters, content plans, push notifications – at least the basis for all this can be obtained from neural networks. And then tighten it yourself, taking into account your needs.
Processing and analysis of large volumes of data
Here the neural network will not be equal in speed and depth of analysis. All you have to do is make a decision based on them.
Writing comments
Commenting is a free method of promoting a product. It can be used on social networks and websites. Conscious comments get a lot of likes, and some users will definitely go to your profile to find out more about you. Plus, the name of your brand will become familiar to the audience and will be remembered. But don’t torment copywriters with this task: artificial intelligence will definitely cope with it just as well.
Generating images and concepts
Instead of boring stock photos, you can use bright and detailed drawings created by AI. In the same way, you can create icons for websites and applications, the basis for designing posts on social networks or blogs, etc.
Let's summarize. Finding balance – the way of the samurai
The general hype around neural networks expectedly subsided by the middle of the year. Elon Musk and Steve Wozniak, the main opinion makers from the IT world, called for stopping further training of neural networks more powerful than GPT-4. And they seemed to listen to them. But all this does not negate the fact that even at the current level, AI technologies show impressive results.
A lull in the news shouldn't make you think the technology has disappeared. Neural networks are the present and future of our world. This is a must-have for any startup and established business. Of course, they are not able to completely replace people, but they will become an effective assistant for the team and your common cause.
In what ratio to distribute tasks between artificial intelligence and real people is a question of the specifics of your field and the competencies of a particular team. But one thing is certain: the list of requirements for an ideal candidate now needs to add the ability to effectively use neural networks as an assistant. Anyone who is afraid or lazy to introduce new tools into their work is doomed to swallow the dust of their competitors in the near future. This is the way.
How are things going with neural networks? What tasks do you use it for, what results can you boast about?
If you want to read more, check out our tg channel “How’s business?”, and to watch interesting videos about business and the development of startups, go to our YouTube channel of the same name.
