1. 1 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search Dave Micek Founder Former President of Search Pioneer Alta Vista Former Head of Texas Instruments Software division CEO/President of three other Technology Companies Jay Martin Founder Over 25 Years of Management Consulting and Industry Original Inventor of Job Search Outsourcing ( JobSerf ) Lead Analyst for IBM ’s Job Matching Application Selected Advisors Peter Gudmundsson Richard Guha Robert Maher CEO of RecruitMilitary, Former CEO of Jobs.com Former Chairman of MENG, ex-SVP of BMC Software Over 35 years of Outplacement & Career Coaching Artificial Intelligence for Job Search 1 Summary Version of Concept Deck

2. 2 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search Reading jobs online is a VERY LARGE, and incredibly costly PROBLEM Job seekers read jobs from the internet each week 40 million + Time spent reading online jobs $ 100 billion/year + 1,000 s of Job Boards combined with even more company sites Online job search requires one to spend inordinate amounts of time reading jobs, with minimal results Incredible amounts of time wasted Some experts discourage it Unemployed out of work longer Employers get fewer candidates The Impacts Wage of the average American $ 25 per hour + Unemployed looking 5 million + The Problem Could a job listing be analyzed in advance to identify & extract its key components? JOBACUS enables finding and applying to jobs, without having to read the details JOBACUS reads/understands a job listing, so you don’t have to 72 % US job seekers visit a job board + 2

3. 3 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search If presented with two job boards to use to search for jobs, which…. …would you choose? One with 4 filters to sort & rank, or one with 8? More accuracy is always better. How about if there was one with 52? Getting HR or Recruiters to enter 52 would be nearly impossible, but… …what if you used Artificial Intelligence to transform any job to enable the 52? Location Level Industry Title 4 Filters Functions Salary Size Visa Status Location Level Industry Title 8 Filters Location Level Industry Title Functions Salary Size Visa Status Languages Education Skills Required Years Experience Relocation Travel 52 Filters Location Level Industry Title Functions Salary Size Visa Status Languages Education Skills Required Years Experience Relocation Travel 52 Filters Location Level Industry Title Functions Salary Size Visa Status Languages Education Skills Required Years Experience Relocation Travel 52 Filters If you had the answers to 52 questions about a job, would you need to read it? 3

4. 4 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search People read jobs for two reasons: A job listing contains 4 sets of relevant data to support these 1. Decision variables – the considerations in deciding to apply 2. Response instructions – the ‘how’ or methods to respond 3. Response content – items for ‘fill-in’ data for a letter or email 4. Custom application requirements – the unpredictable Understand how to apply To decide if they want to apply When a job seeker reads a job listing, they do two things in tandem, almost instantaneously. First, seek to understand ‘what does this mean?’ Second, they ask ‘what does it mean for me?’ JOBACUS uses Artificial Intelligence to capture the first, which is independent of the job seeker. Job Search previously focused on one question 4

5. 5 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search END How do you search millions of jobs ? How do you search millions of jobs for millions of users How do you search millions of jobs for millions of users in thousands of different formats? The Answer is, you don’t need to! 5

6. 6 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search ? END How do you search millions of jobs for millions of users in thousands of different formats? Start with a single job listing.Focus only on the ‘job’ listings first.Extract relevant data from the job.Convert data into standard values. ? Extract & Convert Four Data Sets Decision Variables Response Instructions Response Content ‘Fill-in’ Data Custom Requirements Artificial Intelligence for Job search 5

7. 7 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search END How do you search millions of jobs for millions of users in thousands of different formats? ? Then convert all of the jobsConvert data into standard values. Artificial Intelligence for Job search 5

8. 8 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search END How do you search millions of jobs for millions of users in thousands of different formats? Then convert all of the jobs ? 5

9. 9 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search END Finally, provide a corresponding interface! ? Return the focus to the job seekers. How do you search millions of jobs for millions of users in thousands of different formats? 5

10. 10 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search What are decision variables? The different elements of a job listing that are used to make the decision to apply. Q*(C*J*O) t Apply? J QOC t A mathematical expression shows the primary relationship between the 5 major decision variable groups contained within a job listing. The decision to ‘apply’ is made by comparing these against the company’s qualification requirements, with the preferences and priorities of the job seeker. Q Strength of job seeker’s background as compared to Qualifications C Interest to work at the Company, the location or in environment J Interest in performing the specific Job activities and work schedule O Given the above, interest in the Offer (salary, benefits, etc.) t Burden to properly respond to a job, typically as a function of Time Structured Logic Note: Actual equation ‘to apply’ has hundreds of variables. Includes weightings and relational/dependency variables. 6

11. 11 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search How did we find the decision variables? Our team spent years identifying, prioritizing and structuring them. Mapped out over 215 different potential job listing decision variables. Categorized into our 5 equation variable groups. Identified a ‘cut-off’ at the 52 nd as the comprehensive set needed to arrive at an ‘apply’ decision Decision variables 52 Database fields for processing 126 Variables with a bounded set of options to select 40 + Q*(C*J*O) t Comprehensive set refers to sufficient to allow any job seeker to decide whether to apply The decision variables answer 52 questions, further defined by 126 database fields 40+ of these have fixed sets of values, enabling the use of drop down menus Reviewed field structure of Top 200 Job Boards Identified new variables from over 60,000 jobs Utilized structure/ data from JobSerf & users (10 years) 7

12. 12 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ….. (additional 31 questions) 52 JOBACUS searches for strings for all fields. Strings Related To 52 Answers Job Listing Director, IP & PatentsFrito-Lay Plano, TexasFull-Time The position is an executive role, which requires a J.D. from a top 20 program. The Director will review patent applications, submit information to the USPTO and also advise Marketing on trademark issues. We prefer at least 10 years of prior industry experience in Legal, preferably in Consumer Goods. The job will require excellent analytical skills, and also a degree in Eng. or Food Science. Additional skills include knowledge of Intellectual Property Law and also the inner workings of the USPTO. Advanced Word and Excel skills are also required. Frito-Lay requires a minimum GPA of 3.0 for all candidates from their undergraduate programs. Activities performed in the job include: Evaluating R&D ideas for patentability Writing Patent applications Defending existing Patents & Trademarks The salary range is from 160k-200k/yr., and Directors are eligible for the year-end bonus plan of up to 20%. U.S. citizen or U.S. person is required. The position is not open for Telework. Some travel, up to 40%, may be required. Given the diversity of our team, the candidates are preferred to speak Spanish fluently. Relocation is available for top candidates. Please apply online via the following link. Director, IP & PatentsFrito-Lay Plano, TexasFull-Time The position is an executive role, which requires a J.D. from a top 20 program. The Director will review patent applications, submit information to the USPTO and also advise Marketing on trademark issues. We prefer at least 10 years of prior industry experience in Legal, preferably in Consumer Goods. The job will require excellent analytical skills, and also a degree in Eng. or Food Science. Additional skills include knowledge of Intellectual Property Law and also the inner workings of the USPTO. Advanced Word and Excel skills are also required. Frito-Lay requires a minimum GPA of 3.0 for all candidates from their undergraduate programs. Activities performed in the job include: Evaluating R&D ideas for patentability Writing Patent applications Defending existing Patents & Trademarks The salary range is from 160k-200k/yr., and Directors are eligible for the year-end bonus plan of up to 20%. U.S. citizen or U.S. person is required. The position is not open for Telework. Some travel, up to 40%, may be required. Given the diversity of our team, the candidates are preferred to speak Spanish fluently. Relocation is available for top candidates. Please apply online via the following link. 8

13. 13 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ….. (additional 31 questions) 52 Director, IP & PatentsFrito-Lay Plano, TexasFull-Time The position is an executive role, which requires a J.D. from a top 20 program. The Director will review patent applications, submit information to the USPTO and also advise Marketing on trademark issues. We prefer at least 10 years of prior industry experience in Legal, preferably in Consumer Goods. The job will require excellent analytical skills, and also a degree in Eng. or Food Science. Additional skills include knowledge of Intellectual Property and also the inner workings of the USPTO. Advanced Word and Excel skills are also required. Frito-Lay requires a minimum GPA of 3.0 for all candidates from their undergraduate programs. Activities performed in the job include: Evaluating R&D ideas for patentability Writing Patent applications Defending existing Patents & Trademarks The salary range is from 160k-200k/yr., and Directors are eligible for the year-end bonus plan of up to 20%. U.S. citizen or U.S. person is required. The position is not open for Telework. Some travel, up to 40%, may be required. Given the diversity of our team, the candidates are preferred to speak Spanish fluently. Relocation is available for top candidates. Please apply online via the following link. JOBACUS identifies all relevant text inside the job. Job Listing Strings Related To 52 Answers 8

14. 14 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search 52 Questions Answered 1 Frito-Lay (from company XML field) 2 Company, driven off ‘Frito-Lay’ in a database 3 Plano, Texas (from city & state XML fields) 4 ------- 5 Relocation is available 6 Director, IP & Patents (from title XML field) 7 Director 8 IP, Patents (from title XML field) 9 Driven off Frito-Lay (company XML field) 10 requires a J.D. / degree in Eng. or Food Science 11 requires a J.D. / degree in Eng. or Food Science 12 requires a minimum GPA of 3.0 13 Full-Time (from type XML field) 14 salary range is from 160k-200k/yr 15 eligible for the year-end bonus plan of up to 20% 16 are preferred to speak Spanish fluently 17 prefer at least 10 years of prior industry experience 18 ---------- 19 analytical skills, knowledge of Intellectual Property Law, the inner workings of the USPTO, Word, Excel 20 is not open for Telework ….. (additional 31 questions) 52 apply online via the following link The strings/logic will ‘answer’ our 52 questions. 1 Frito-Lay 2 Company 3 Plano, Texas 4 ------- 5 Yes 6 Director, IP & Patents 7 Director 8 Legal 9 Consumer Goods 10 Doctorate / Bachelors 11 Law, Engineering, Food Science 12 3.0 13 Full-Time 14 160,000 to 200,000 15 Bonus 20% 16 Spanish is preferred spoken fluently 17 10+ Years 18 ---------- 19 analytical skills, knowledge of Intellectual Property Law, the inner workings of the USPTO, Word, Excel 20 No ….. (additional 31 questions) 52 Online Application Strings Related To 52 Answers 8

15. 15 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search 1 Frito-Lay 2 Company 3 Plano, Texas 4 ------- 5 Yes 6 Director, IP & Patents 7 Director 8 Legal 9 Consumer Goods 10 DoctorateBachelors 11 LawEngineeringFood Science 12 3.0 13 Full-Time 14 160,000200,000 15 Bonus 20% 16 SpanishPreferSpeakFluent 17 10+ Years 18 ---------- 19 analytical skillsIntellectual Property LawUSPTO WordExcel 20 No ….. (additional 31 questions) 52 Online Application 1 Frito-Lay 2 Company 3 Plano, Texas 4 ------- 5 Yes 6 Director, IP & Patents 7 Director 8 Legal 9 Consumer Goods 10 Doctorate / Bachelors 11 Law, Engineering, Food Science 12 3.0 13 Full-Time 14 160,000 to 200,000 15 Bonus 20% 16 Spanish is preferred spoken fluently 17 10+ Years 18 ---------- 19 analytical skills, knowledge of Intellectual Property Law, the inner workings of the USPTO, Word, Excel 20 No ….. (additional 31 questions) 52 Online Application These answers drive the 126 field values. 52 Questions – 126 Fields 52 Questions Answered 8

16. 16 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search 50 Fields Defined. JOBACUS is designed to translate any job listing. Director, IP & PatentsFrito-Lay Plano, TexasFull-Time The position is an executive role, which requires a J.D. from a top 20 program. The Director will review patent applications, submit information to the USPTO and also advise Marketing on trademark issues. We prefer at least 10 years of prior industry experience in Legal, preferably in Consumer Goods. The job will require excellent analytical skills, and also a degree in Eng. or Food Science. Additional skills include knowledge of Intellectual Property Law and also the inner workings of the USPTO. Advanced Word and Excel skills are also required. Frito-Lay requires a minimum GPA of 3.0 for all candidates from their undergraduate programs. Activities performed in the job include: Evaluating R&D ideas for patentability Writing Patent applications Defending existing Patents & Trademarks The salary range is from 160k-200k/yr., and Directors are eligible for the year-end bonus plan of up to 20%. U.S. citizen or U.S. person is required. The position is not open for Telework. Some travel, up to 40%, may be required. Given the diversity of our team, the candidates are preferred to speak Spanish fluently. Relocation is available for top candidates. Please apply online via the following link. 1 Frito-Lay 2 Company 3 Plano, Texas 4 ------- 5 Yes 6 Director, IP & Patents 7 Director 8 Legal 9 Consumer Goods 10 DoctorateBachelors 11 LawEngineeringFood Science 12 3.0 13 Full-Time 14 160,000200,000 15 Bonus 20% 16 SpanishPreferSpeakFluent 17 10+ Years 18 ---------- 19 analytical skillsIntellectual Property LawUSPTO WordExcel 20 No ….. (additional 31 questions) 52 Online Application Job Listing 52 Questions Answered Using 126 Fields 9

17. 17 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search JOBACUS uses four technologies to drive towards 100% accuracy of the translation of the job listing into our 52 decision variables. Fail to Identify a Field Identify Wrong Value 100% Perfect These are the two major classes of errors from first three technologies User Validation allows us to reach close to 100% accuracy. Comparative String Matching Translate thru Boolean Logic Natural Language Processing User Validation Comparative Strings will define most fields, but the three other methods will help translate the job as accurately as possible 12 Use Cases using variants of Boolean logic are used after String Matching 4 NLP is envisioned to review any phrases or sentences in which the first two technologies do not identify any field values 3 2 1 10

18. 18 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search What problems does JOBACUS solve? Matching Application Efficiency Mobile Duplicates Non-Jobs Employers Filtering & ranking accuracy across 52 areas Mechanically able to build responses Queue by time/burden needed to apply Smaller data set enables smaller screens System analysis filters out duplicate jobs Advertisements identified/filtered out Motivates job seekers to supply ‘good’ data 18. JOBACUS solves all of the major problems of the job seeker, plus solves the employers’ #1 as well. 11

19. 19 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search And finally, our Lake Analogy shows how JOBACUS compares to existing solutions. Lets them waste all weekend fishing (or reading online advertisements) Points them to areas of the lake that might have the right fish Gives them an idea on what type of bait and depths to try Existing online job websites are similar to a fishing boat marina on a lake. 19 Loans the job seeker a boat and fishing rod 12

20. 20 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search JOBACUS utilizes a far more effective approach to solve the same problem. Invites you over to the counter at their fish market, and asks.. Takes out all the fish, sorts by type Drains the lake before you get there Cleans, scales and filets them all “Here are our fish, which one would you like?” 20 13

21. 21 Jay Martin Summer 2015 JOBACUS Concept.ppt Artificial Intelligence for Job Search Summary – This is the short-version Thank you for reading about JOBACUS This deck was created to explain the JOBACUS concept. We have a separate partner deck describing the different business models. We have already filed the patents, built a prototype, and are seeking a partner to finalize the logic, build out the interfaces and launch it. JOBACUS shows how we can permanently solve online job search. Please follow us on Twitter, more followers helps us demonstrate interest to finish it. We can be contacted at: Jay Martin JOBACUS, Founder, (214) 520-8019, jay@jobacus.comjay@jobacus.com 21 @BuildJOBACUS www.jobacus.com 14 JOBACUS is grateful to have one of the country’s top graphic design talents as part of our team. James Suh http://jamessuh.net/