Is AI A Waste Of Time In Recruitment?

What is going on in your head?

Recruiters know how overwhelming it can be trying to find a candidate when the job market is contracting and the number of prospective candidates applying can usually number over 200, if not more during tougher times. Finding them is hard, working through them can be considered laborious.

These CVs are then whittled down, contact made, phone calls, video chats and then more interviews. And if none of the candidates are up to snuff, then the recruiter must start the whole process all over again. Then there are the back-and-forth meetings and calls and emails and reports for the client.

You can understand why many folks in the industry would consider AI as a panacea for their ills. Automation of repetitive tasks such as scheduling and screening. There is an idea that it can also reduce bias but, as we have noted in the past, that is a tricky thing to eliminate if the program has been created by a human originally, and, of course, they always are created by humans, since AI has not yet become as sophisticated enough to develop ones on its own.

Apart from that problem, there are other pitfalls within this strategy. While it can work through tons of data on job boards, it can only seek thanks to lists of short key words. This is helpful because it saves many work hours, so that the humans can be busy with other important tasks, and can compile data from different sites. The great plan can fall apart due to the fact that, unlike humans, AI cannot evaluate how good a CV actually is. The content within resumes, to our brains, which are basically fleshy supercomputers, is easily absorbed and evaluated on many levels such as grammar, logic, questionable information and sensible career progression. When we read a CV, we are using all of our years of experience living with humans to work out whether the person behind the CV is the one we require to fill this position. We can read something jargony or slangy and understand, or figure out, what it means even if we haven’t encountered it before.

AI can only looks for the key word or mistakes that it has been told to look for. Everything else is not taken on board as being relevant. The AI can become inefficient if recruiters must refine constantly, especially if geography is concerned.

We are not trying to be down on AI. Hell, we love AI and the innovations our amazing clients make within that space. The point we are making is that AI is great for certain things and on other tasks, it has still got a long way to come.

To put it another way, we believe in people power. We believe that, even when AI becomes much more powerful and can fill in for recruiters in some aspects, it will never have that human element, some would describe as indefinable. Our clients make a difference because they have the best humans, found by great human recruiters, to help make that difference. Only with the perfect staff for an AI project, can that project excel. And only with gains made there, can AI reach a height where it is then able to possibly find candidates.

People are at the heart of what we do. Utilising their expertise to get the job done right. AI is a tool that can help but in a business, like recruitment, which is about human communication and human potential, the best tools will always be the ones that keep humans front and centre.

Curious about how Zenshin Talent can help your organisation? Contact us today for a no-strings conversation about your needs and our experience.

Responsive Employers = Respected Employees

It really adds up to treat your team like human beings

A business which conducts itself with purpose and professionalism naturally elevates itself above the competition. A relentless drive to increase in size in order to satisfy shareholders can serve to reduce the people who work there to figures, robots even.

Whether a company chooses to take this route or not, will define its future. Thankfully, more companies are adopting the path towards a mission that is not just based on money, but on treating employees with respect, acknowledging that they hold the keys to the future of the business.

Seeking meaning through actions is what humans do, and work is no different. Yes, we all want to be sufficiently recompensed for our time, and perks are nice to have too, but the realising of potential and a sense of contributing meaningfully are major factors in the long-term mental well-being of employees. Allowing workers to learn and grow means the good of the company goes beyond fulfilling the goals of the business but can emerge out into the society around it, benefitting those who may be outside of the immediate area of influence.

When it comes to recruitment, it is easy to spot employers who are engaged. It can be as simple as hiring managers replying to emails or responding to candidate resumes in a timely fashion. For all the sound and fury surrounding the search for new prospects to fill job roles, if what follows the flurry of activity is the metaphorical sound of crickets, a specialist recruitment partner starts to begin to understand why the hiring has been a long drawn out process so far.

But just because an employer isn’t engaged with these issues doesn’t mean they don’t want to be. It can be difficult asking for help when you don’t really know what kind of help you need or how to go about starting the process.

Finding support throughout this can be hard, if you are starting from scratch, as an organisation has either made steps towards being responsive and responsible, or it hasn’t. If it hasn’t, then it can feel like an uphill struggle. All companies make noises about listening to their employees but the difference between intending to do something and actually going through with it, is huge.

Processes and systems need to be in place, and putting them there takes time. Companies can and do change but change is often slow-paced. Relationships can be complex and there may be a lot to unpack.

Having an experienced specialist recruitment expert onside can help greatly. They will have experience of sorting the strategy for onboarding new candidates within your sector, will possess knowledge of the values shared by all of the different generations you may be recruiting and they can promote your new way of doing things to the candidates as if they are an external observer.

Within Data, AI and Cloud, it is important to view new technology as a way to enhance the potential of your workforce rather than a way of enslaving them to an omnipresent company presence. There will always be doubters who misunderstand the aims, or those who are old-school who attempt to mould what is happening to fit their standard worldview. Specialist recruitment partners are outside and have a better overview of how things are going and where things may be going wrong.

Responsive businesses will treat all the people in and around the business with dignity, pays fairly, challenges and reassesses its values in the face of criticism, develops an environment of accountability and nurturing where people can thrive and will help the company thrive, in return.

Companies must adapt during these times. Showing appreciation, encouragement and consideration is not a weakness. Getting fully involved in the recruitment should not draw you away from your current responsibilities. If you have the right help on your side, these problems will not even be a concern anymore.

Curious about how Zenshin Talent can help your organisation? Contact us today for a no-strings conversation about your needs and our experience.

Does Your AI Strategy Make Sense?

AI should be handled intelligently

Artificial Intelligence projects that are coming back online after stalling during the pandemic need careful consideration or they risk falling apart, according to a new report.

The Gartner report states that a strong AI engineering strategy is required by companies to ensure there are no failures within AI projects. The proof-of-concept stage must lead on to full roll-out of the project and to make this happen, strategies must not fall by the wayside.

Obviously, before you embark on an AI strategy, you should really undertake a ‘proof of value’ assessment on the viability of the project and whether it will meet business needs. Of course, PoVs are not where you define the problem, just where you, as the name suggests, prove the value.

AI projects usually fall apart due to lack of maintenance, the inability to scale and failure to govern correctly. A strong strategy will overcome these problems, justifying the investment and helping the project become reliable and easier to interpret.

Briefly, the three areas that must be dealt with are:

  1. Data – the collection, cleaning and arrangement of data is imperative. If this stage is not taken seriously enough, you will have long-term impacts further down the line.
  2. Machine Learning – the training, testing and fine tuning of the algorithm the team has designed and built.
  3. Artificial Intelligence – the AI comes in to play in order to use the data. This must be deployed and closely monitored.

The storage and accessibility of your data should also be understood. Are you working from physical servers or are you using the cloud? What is your security like on the cloud side? Also, have you factored in QA throughout the whole project?

Apart from cloud security, you should always be watchful over all of your data, no matter where it is. Some businesses will be outsourcing tasks but regardless, the data should not be sensitive data and should be treated with the utmost respect.

AI engineering draws together the disciplines of DevOps, ModelOps and DataOps. DevOps is about the speed of changes in code, data or models and is important in AI projects where variables are the norm and this discipline is used for data in DataOps and ML in ModelOps.

A lot of companies, emerging from the Covid-19 pandemic, are engaging in ‘responsible AI’, which takes in trust, accountability, compliance, risk, transparency and fairness, amongst other things. This marks a change from viewing AI as something ‘other’, to understanding that it is now an inseparable part of the business, and thus, must be held to the same standards. As Gartner says, every company is now a technology company.

With companies in the situations they are in, regarding the pandemic, it is understandable that they are chomping at the bit to get going, but speeding ahead without the correct planning would be a mistake. Plans that seemed solid prior the Covid-19 should be reassessed, in light of changing priorities within the business and what has been learned about the business in these testing times.

We have not even mentioned the team yet either, as the success of AI projects stands or falls on the quality of the team involved. This will require a dedicated recruiter, to track down the key players in order to create an AI project fit for the new era of your company.

Curious about how Zenshin Talent can help your organisation? Contact us today for a no-strings conversation about your needs and our experience.

Over-interviewing Is Killing Your Business

Driving away great, qualified candidates is the ultimate facepalm

You may not want to hear it. You may cover your ears and hide from it. You may avoid anyone who is trying to tell you this, but you have to face facts. When it comes to AI, Machine Learning and Data Science, quality candidates are currently swamped with offers. This is no longer a buyer’s market.

Yet still businesses are acting like they have all the time in the world to find the skilled individuals or teams that will make their data projects happen. One could put it down to burying their heads in the ground, one could allow for the company being slow to identify and fix problems, one could consider that to some, this is just how recruitment is: a long drawn-out experience.

But let’s imagine your firm doesn’t actually want to lose prime candidates, causing work and projects to back up, money draining away. Let’s imagine that you don’t have that much time to waste. How can you avoid this happening to you?

Well, firstly, you need to actually acknowledge that you have a gut. We’re not talking about any lockdown weight you might have put on. We are talking about that sense you have when something is wrong or right. Without using your gut, especially within data recruitment, you are in for a world of pain.

Look, we understand that Covid-19 has complicated hiring. Doing video interviews can be a pain and they can really take some getting used to. Poor internet connection or worrying about the webcam that is pointing right up your nose can distract you from taking in everything the prospect is saying. This can only improve with practice.

Do you know how well some companies are doing at hiring during these times? One company we know of makes offers after one video interview. How can this be? Because they are organised, they are cool and they are going with their gut when it comes to the hire. Ask yourself: would you or could you forgive a bad video interview? Would you display the same courtesy to the candidate that they would to you if you were having technical issues or were nervous about whether the room they are speaking to you from looks a mess or not?

Without understanding, and gut instinct, this process will not be easy on you. It is a fact, in many cases, that businesses are over-interviewing because they can’t interview in the office. Is it feasible to do face-to-face? With lockdown easing, there are workarounds, as long as you bear in mind the safety concerns.

The amount of stages within the interviews are growing, due mainly to hesitancy to just make a decision. What do you think is reasonable? When you were at school, did you love taking tests? Well guess what? Adults don’t like it either. Sometimes you have to make a candidate take a test and that is fair enough, but multiple tests, no matter the purpose, feel excessive for the candidate. For candidates receiving multiple offers, it is downright crazy to do this.

What does it say about your company when your competitor can wrap up the process in two steps? Your lack of consideration for your processes is killing candidates’ perception of your organisation

Take some responsibility. Don’t pass the buck by saying “Oh I like him/her but what do you think?” Why should a candidate sign up for a job where the managers refuse to commit to a course of action? It is fair to say that the prospect, when imagining what it would be like to work for you, will not imagine a company that can deliver on its promises even if it really wants to.

Long-winded and inflexible hiring practices lead to a paralysis of projects which leads to desperation further down the line. While you are holding off on hiring, waiting for that imaginary, perfect candidate you haven’t even met yet, the great candidates you have met will lose patience with you and go elsewhere.

So what are you going to do about it?

Curious about how Zenshin Talent can help your organisation? Contact us today for a no-strings conversation about your needs and our experience.

The Dangers Of Recruiting With AI And Machine Learning

AI has its uses but it should not be treated as a solution for everything

Whilst we recruit Machine Learning and Data experts for other companies, the actual use of Machine Learning for recruiting purposes is highly problematic. It may seem crazy that recruiters working within this sector would question ML, but because we know this subject, it makes perfect sense to us.

Yes, technology helps us recruiter in some ways, but the idea of a one-size-fits-all solution is the incorrect reading of the situation. Tech can help us find new ways to reach out to the right candidates but when it comes to finding and selecting who is perfect for the role, it lacks the natural element, that understanding that comes with interacting with those kinds of candidates, working with those businesses, researching the roles. It lacks a human touch, that extra sense that is sometimes indefinable.

Would you buy a house with no human interaction whatsoever? Yes you can look at the pretty pictures, you can even walk around it. But if no one was talking to you about the house, if you couldn’t meet the owners and gauge them, if you couldn’t get a sense of what it is like to actually live there, something just wouldn’t feel right. Finding a job, or finding the right individual to fill a role, is a really big deal. No one goes into it lightly and rightfully so. Selections made via automated algorithm can seem right but scratching beneath the surface reveals a more complicated situation.

The idea that most people have, and one which drives the concept of using AI to dominate the recruiting process, is that machines have no bias. It is true that machines do not have emotions and if that were the only factor, then it would be understandable that you would take that route with your recruitment. The problem is that machines need to be fed facts by humans. Biased humans equal biased data equal biased AI decisions.

The Amazon gender bias story from 2018 highlights this. Amazon were seeking a system to simplify the process, where they could input a lot of CVs and the machine would select the top five based on a rating system. The problem was that the machine could only base its future predictions on past actions. Amazon realised that, because the past ten years had been dominated by male applicants, the AI had a bias against female applicants.

The Amazon debacle happened with correctly inputted data. If the data is inputted incorrectly or is formatted in a way that the system cannot read it, that information will be missing from the final decision. There is no universal format for a resume, so you can imagine the problems that could ensue there. Sometimes people just are not very good at writing their CV. They may miss out something that the AI is searching for. There may be a spelling error. They may possess extraordinary skills but few qualifications. The AI can only view the information in a way that it has been instructed to. It is fascinating when you start to think of all of the things you can pick up from a resume instinctively, and if you had to tell someone else your thought process, you would be there for a week, because you would have to impart the stories of all the place and situations in which you learned those things. Suffice it to say, there isn’t enough time to teach a machine what is inside your head.

And all of that is before you even get to the emotionless impersonality of it all, the lack of understanding when it comes to personality and the way machines struggle to process the ever-evolving and complicated rules of slang.

Here at Zenshin Talent we embrace AI and ML to help us target the right candidates in a more efficient way. The other element we always include is our human understanding, using it to nurture the client and candidate relationships in order to ensure the correct match.

Curious about how Zenshin Talent can help your organisation? Contact us today for a no-strings conversation about your needs and our experience.

Why Do You Need Cloud Data?

Could there be a silver lining on your data cloud?

These days, data is integral to successful companies and accessing, tracking, reporting on and storing large amounts of data gives the forward-thinking business a distinct advantage. While a lot of firms are still storing their data on their own servers, accessible via traditional methods, modern ones recognise the logistical benefits of cloud data.

With astronomical amounts of data being created each and every day, you can choose to embrace it now, or risk being left behind as your competitors move ahead of you. What is your strategy to manage your data? Well, first, you must recognise what data you currently possess. You must have a structure in place to deal with it.

Firstly, you must deal with the availability of your data. Your data scientists must be on top of collating, controlling and shaping the data into something that is actually useable within your business. Data can fly around at different speeds and in different forms that must be processed into something comparable which equals real value for your company.

We are really talking about speed here. Your company should be able to access the data quickly, it must be accessible through one channel, so people aren’t having to waste time going to multiple sources and this can drive real-time decisions.

As you take steps to move your data to the cloud, your current data structure should be updated and refined to make the move smoother. Security is definitely a priority and if yours is lacking in any way, it must be evaluated and reinforced. Possibly engage a managed service partner and automate backups to reduce overall costs. Each solution will be slightly different, depending on the type of business, the types of data that needs to be managed and the level of security needed.

It is easier to survey and identify problems and gaps in your solution if you operate with data at the forefront of your cloud plans. With this overview you can see what data is going to waste and can rectify that problem. As cloud is the future, when new opportunities present themselves, you will be at the leading edge when it comes to data exploitation.

When introducing AI to the mix, the cloud aspect makes even more sense. With the compartmentalisation and availability of the data and the speedy availability and deliverability, analysis happens quickly and accurately, leading AI to utilise the data to achieve your goals, which saves time and money in the long-run. As we stated before, it is about making that data as easily available as possible so that your company can truly benefit from the data it owns to build models and predict behaviours, to drive sales and keep costs low.

Collaboration, and ultimately monetisation, is also possible due to the cloud. Offering controlled access to partner companies can benefit both parties of the project matches mutual needs. Prior to the cloud, this type of sharing was fraught with difficulties and could become dangerous due to the lack of security protocols. With the measures in place with the cloud, this is much safer now. Companies within a sector like retail have data that can be shared and monetised, as long as this is done ethically. Product performance is one such example of how this shared data can benefit both parties, helping the supplier to improve pricing or promotion. While this won’t work for every company, it certainly has its proponents.

To create as seamless a transition as possible, from traditional data storage and usage, you must employ the right team, a team with experience that knows the easiest route through. With that team in place, the future of your business will be secured.

Curious about how Zenshin Talent can help your organisation hire the best candidates? Contact us today for a no-strings conversation about your needs and our experience.