The Human Development Index (HDI) is calculated using normalized indicators from three dimensions- health, education, and standard of living (or income). This paper evaluates three aggregation methods of computing HDI using a set of axioms. The old measure of HDI taking a linear average of the three dimensions satisfies monotonicity, anonymity, and normalization (or MAN) axioms. The current geometric mean approach additionally satisfies the axioms of uniformity, which penalizes unbalanced or skewed development across dimensions. We propose an alternative measure, where HDI is the additive inverse of the distance from the ideal. This measure, in addition to the above-mentioned axioms, also satisfies shortfall sensitivity (the emphasis on the neglected dimension should be at least in proportion to the shortfall) and hiatus sensitivity to level (higher overall attainment must simultaneously lead to reduction in gap across dimensions). An acronym of these axioms is MANUSH, which incidentally means human in some of the South Asians languages and the alphabets can also be rearranged to denote HUMANS. Using Minkowski distance function we also give an α-class of measures, special cases of which turn out to be the old linear averaging method (α=1) and our proposed displaced ideal measure (α=2) and when α≥2 then these class of measures also satisfy the MANUSH axioms.