The Case for A New Resume

Nidhi Hebbar
Oct 15, 2019 · 11 min read

Traditional resumes value superficial achievements at the expense of meaningful capabilities, and it is no coincidence that this is what our societies produce around the world. To develop holistically capable individuals we need new evaluative methods that keep pace with the skills we value today.

From research and conversations with educators, learners, and companies around the world, I propose key components and considerations for a new resume paradigm, and the ways in which technology can help make this feasible.


The skills we value have changed.

What is holding us back from focusing on the new skills?

We have a global skills gap. The skills society demands are not the skills most individuals have developed in both school and life. This is further exacerbated by our inability to effectively showcase the skills we care about. After all, we still use the traditional resume for almost everything — one that prioritizes superficial titles rather than real evidence of 21st century skills.

In every global or economic report, there are warnings of this growing skills gap around the world. Companies have unfilled jobs that drain time and money to fill, students (especially from under-resourced families) graduate without employable skills nor the ability to employ themselves, and schools are producing the largest global workforce ever that will lack the skills we value tomorrow. Across schools in every country I’ve worked with, from Sweden to Singapore, India to Kenya, educators struggle to equip students with skills they need in a rapidly changing world. These 21st century skills–the ability to think critically and creatively, to motivate and lead a team — are the same skills companies struggle to find in candidates around the world. This is even more obvious in economies like that of Kenya or India where there is simultaneous mass unemployment, high-potential human capital, and unfilled employment opportunities. A new resume paradigm, focused on evidence not titles, could motivate a shift in both the way we value the right capabilities and the way learners learn (so that they can build them).

Why we must move past the old resume

By using the traditional resume as the gold standard for evaluating a person’s potential, we prioritize superficial brands and titles rather than meaningful skills. Take a look at the resumes below.

Which candidate would you hire?

Sabine’s resume (left) reads beautifully with four big brands, and bullets that describe her teams’ work — supporting developing countries, large corporations, and high-profile Facebook features. James’ resume is interesting, but not traditionally impressive. Nobody’s heard of the companies on his resume, and bullets don’t do justice to the value he brings. Sabine’s and James’ LinkedIn profiles give the same impression.

In reality, Sabine is missing important skills, and James is lost talent. Sabine took expensive SAT classes in high school and went to Harvard without critically thinking about why or what she learned. After college, she made coffee runs and scanned documents for policy analysts at the World Bank, made presentations for micro-managing partners at McKinsey, and worked as a mediocre project manager at Facebook. She received 3 out of 5 Needs Improvement ratings on her last review which prompted her to apply for new jobs. James built a water filtration system in high school that detected critical levels (statistics) of harmful toxins (science) in tap water and distributed (collaboration) the low-cost product (economics) to his community. He was even interviewed on a local podcast requiring self-reflection and effective communication. After attending a state college, James moved to Thailand to build out a company that shares sustainable practices between local farmers, then analyzed the societal impact of technologies at a global think tank in the UK. He devised innovative international business strategies, navigated regulatory and political environments, and motivated large teams without officially managing them.


How might we better demonstrate our abilities?

What new methods could enable us to showcase meaningful skills?

A New Resume Paradigm

James must be able to paint a story of his life — in audio reflections, marketing materials, pictures of his water filtration device, visualizations of the dramatic rise in farmers’ income data, or a progression of strategy diagrams. Teachers or hiring organizations could see evidence of his curiosity, creative solutions, and the lasting impression he made on coworkers and mentors who would vouch for both his significant contributions and invaluable soft skills. If schools and jobs emphasize such meaningful evidence, individuals would prioritize building these skills.

Sabine might be hard-pressed to find artifacts that meaningfully demonstrate her work in this format, and coworker reviews would reveal the true nature of her contributions. While this may not sound ideal, if high school transcripts and college entrance exams valued the right skills, Sabine and her teachers could have proactively identified gaps in her skillset, challenging her to self-reflect and develop stronger critical thinking and communication skills from the start.

Three Necessary Components

In my role building products for education at Apple, I spent years investigating the missing toolkits schools and communities need to shift to their ideal future. We asked hundreds of innovative schools and companies, skills development organizations, learning scientists, and emerging technologists: How do you evaluate skills? How do you demonstrate learning? It quickly became clear that traditional methods — resumes, test scores, and transcripts are no longer sufficient.

My explorations around the world uncovered three components necessary for a new resume paradigm. The ever-changing future was top of mind for most schools and communities, placing emphasis on the below as stable, reliable assessments that could withstand rapid change. At the core of most perspectives was the desire to highlight a somewhat elusive skillset for success and at the same time enable insight for self-reflection and continuous growth (#1 and #3). Answers typically fell into one or more of the below three areas:

  1. How a person thinks. Evidence of process in addition to output is needed to shed meaningful light on one’s ability to learn, think critically, explore assumptions, and construct solutions. Immersive artifacts like photos, videos, or diagrams that expose a candidate’s ability to self-reflect, contextualize, or articulate their work can showcase a candidate’s thought process, progress, and, most importantly, tangible problem solving abilities. Through a student’s process, teachers can identify gaps in understanding and employers can be sure to hire high quality thinkers.
  2. What a person is capable of doing. This is the focus on output, on evidence — what a person has created, designed, or executed. Resumes only give us a list of bullets. Multi-media evidence can show rather than tell an employer what a candidate has actually designed, created, or executed. Such evidence creates a more honest, holistic picture of a candidate’s work and enables students to take ownership of their story, curating and articulating their accomplishments over time.
  3. How we work with others. This is perhaps the most important yet most rare. Companies demand openly self-aware, courageously curious, and compassionately collaborative employees to carry them into an ever-changing future. Portfolios have been used for decades, but soft skills are rarely included. Endorsements, recommendations, and feedback from many coworkers can help to evaluate soft skills in a human and scalable way. For example, data collected internally during company performance reviews would be invaluable insight to a future employer. Such perspectives (with an individual’s consent) could finally replace biased and somewhat nominal reference checks.
For illustration only: a new resume format might include multi-media evidence and social endorsements of critical “soft” skills.

Many schools and industries have shied away from embracing this approach due to the tedious nature of collecting and organizing artifacts across years, various file types, and large amounts of qualitative and quantitative data on an individual. But emerging technologies can play an enormous role in making these approaches feasible and accessible around the world.


How can technology help?

How might technology make these new approaches more feasible and accessible around the world?

Technology has in large part focused on making our current system more efficient, making it easier for teachers to grade multiple-choice tests or for HR departments to screen for keywords; technology personalized learning so that students can more quickly memorize basic math they “need” to know and sites have popped up that auto-generate bullets for your resume. These advances have been somewhat helpful, arguably most importantly because they give teachers time back to focus more on students (and maybe get some sleep). But without the ability to assess and demonstrate new skills, it’s challenging to ask schools or individuals to shift. Technology can unlock new ways to evaluate and demonstrate the skills we actually care about.

Stitching Together Evidence with AI

It probably feels inconceivable to expect students or candidates to diligently document their learning and work processes, and then later stitch together millions of pieces of evidence, accumulated over a lifetime in the form of photos, videos, and data. Artificial Intelligence can help us sort through these artifacts to find the right minute in our audio recordings, compare changes in photos or strategy diagrams, and create visualizations from our recorded data logs. This is necessary for all industries, not just art and design. Based on time stamps, file types, subject areas, project elements, collaborators, and an abundance of other attributes, AI could intelligently tag and organize media files for student portfolios and evaluation by a teacher.

AI could surface James’ artifacts that reflect farmer data — across visual, audio, and data file formats.

Validating The Worth of A Credential with Machine Learning

Blockchain applications today have focused on verifying whether candidates truly have a credential, but it may be more critical for technology to assess the the value of a granted credential. The need to upskill created a massive market of credential providers, resulting in an abundance of (micro)credentials with murky credibility. For example, if an individual has earned a data science credential, have they been able to employ these skills in practice? In countries with the next billion users, saturated higher education systems mean even college gradates often need additional credentials to find work opportunities. The numbers are remarkable. Credentials might be validated by evidence or endorsed by others who have witnessed an individual use their skills in action. Machine learning algorithms might combine both evidence and endorsements to deduce the true value of skills development rather than credentials earned.

A new resume format might be organized around skills rather than companies — showcasing credentials, references, and evidence of a particular skill in a single place.

Assessing Soft Skills with NLP and Blockchain Technologies

According to 2018 and 2019 Global LinkedIn Reports, only 41% of companies have a formal process in place to evaluate soft skills, although the training for soft skills is the #1 priority for talent development. Teachers too have a hard time assessing soft skills that are arguably more valuable than students’ abilities to pass a multiple-choice test. Crowd-sourcing coworker reviews across a wide network would incorporate a human perspective of a candidate’s soft skills. LinkedIn endorsements and recommendations help, but recruiters and schools tell me they find it hard to utilize these features. Blockchain technologies for reviews, could validate important soft skills for which credentials don’t yet exist, and Natural Language Processing could be used to parse large sets of recommendations to meaningfully assess strengths and weaknesses.

Soft skills have become top of mind for the global workforce. They should have a prominent place in a new resume format.

Why not expect more out of technology? Rather than building products to reinforce a system we know is not serving us well, we should instead leverage technology help us redesign the system. The skills society values today are complex to develop and even harder to evaluate. Such technologies make it feasible to consider more meaningful resume formats for schools, companies, and communities.


Now What?

How do we make this happen? What else must we consider?

A fundamental shift in the way we evaluate skills must happen at all levels of the ecosystem: in schools, universities, within upskilling institutions, communities, and employer networks. We would expect such a shift to bring tremendous value for talent acquisition and thus motivate the latter group (employers, communities, and upskillers) to shift more quickly on their own. This would create demand for the technologies and toolkits that make it possible to incorporate real evidence and human perspectives when evaluating a candidate’s potential. The need for diversity at these organizations can hopefully drive new technologies to be created in an equitable and accessible way, but it won’t happen by accident. Below are important design principles to consider in the transition to a new resume paradigm:

Privacy and Biases

A new resume paradigm will leverage immense amounts of new data. It’s critical that individuals are the owners of this data, with full, transparent control over when and with whom specific pieces of information are shared, stored, or deleted. While we know our current assessment and recruiting practices are entrenched in biases, the introduction of tech-based evaluation systems will introduce opportunities to both increase and decrease biases in the system. Our algorithms must be designed from the start with a critical eye towards the way we evaluate cultural and demographic differences.

Open Data Standards and Integrations

Ideally, a new resume will accept a variety of file formats, from mobile photo albums to niche podcasting or geo-mapping software. Establishing open data standards for these new data types (project files, endorsements, skills tags) will encourage substantial adoption of a new resume format, increasing reviewer participation and accuracy of candidate data. This may sound counterproductive to tech company business model, but with sufficient adoption, there’s great opportunity to layer on B2B talent management services that integrate with existing systems and embrace a holistic view of employees.

Mobile and Accessible

Ensuring the new resume is mobile-friendly, accessible, and device-agnostic will enable adoption across countries, demographics, and generations. The universality of MS Word at work, school, home and libraries made it easy for (nearly) anyone to apply for a job. Google Docs made simultaneous collaboration non-negotiable. The new resume format should leverage accessibility advancements such that neurodiverse populations can edit text, seamlessly integrate media artifacts, contribute recommendations, and evaluate credentials for free, while on the go. Mobile friendly formats are more accessible for the next billion users who will come online via mobile networks in India, China, and countries across Africa and Southeast Asia.

For Companies

Assuming we have portfolio artifacts for evidence, crowdsourced endorsements, course data, and recommendations, carefully crafted machine learning algorithms can help companies take a more holistic first pass at candidates than basic keyword searches that are employed today. Human evaluation is still important, but is not necessary at every stage. Again, this is admittedly an incredibly complex and nuanced challenge — models would need to account for the impact of cultural differences, quality of artifacts, and regularly check for biases against certain demographics or input types.

For Schools

To enable a truly systemic shift, public schools and policymakers must have a voice in the creation of such technologies so that they are also designed to learners’ needs too, rather than simply applying them to school settings once built. Unfortunately, schools may take the longest to join (or be heard) in the conversation due to existing assessment structures. Explicit, forward-looking policies must support schools to change the nature of assessment. The same way that No Child Left Behind ushered in an era of standardized tests based on an underlying notion of what students should know, new policies can mandate more holistic assessment methods that prioritize the development of 21st century skills we know to be important — informed by the needs of learners rather than those of our current system.

People of all ages today must learn to find and solve problems, motivate teams and drive their own work, derive insights from data and make connections across international trends. What formats have you found useful for adequately demonstrating these skills?

Nidhi Hebbar

Written by

education ramblings, all about school love, teachers and learners know best, ed-technologist, and design-thinker

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